{"format": "ta-amps.seed-pack.nouns.v1", "pack_id": "code-composition", "status": "proposal_only", "records": [
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.pack", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.skill_pack", "pack:code-composition", "role:pack", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.skill_pack", "role": "pack", "pack": "code-composition", "pack_version": "0.2.0", "title": "A collection of nouns and verbs for composing verified code without rewriting it", "lets_workers": ["Write a small declarative recipe that wires prewritten, tested code nodes together, instead of writing new code for routine data steps.", "Compile a recipe into a checked graph: unknown nodes, wrong port types, bad parameters, missing wiring and cycles are refused with typed diagnostics before anything runs.", "Run a compiled recipe with no model calls, reuse the cached results of unchanged upstream steps, and prove that the emitted standalone Python gives byte-identical outputs.", "Check that a local copy of the code matches this pack's pins: folder digest, module digests, node digests and built-in tests.", "Compare a baseline recipe with a variant by their receipts, and propose a reviewed new node when the catalog lacks a capability."], "flow": ["verify-tools checks a library checkout's code folder against the pins, once per sandbox.", "compose-recipe turns a goal into a recipe candidate that compiles.", "compile-recipe compiles a pinned recipe and records its plan digest.", "run-recipe executes it with pinned inputs and records the receipt.", "compare-runs compares a baseline and a variant by their receipts.", "propose-node, then review-node by a different worker or a person, when no node fits."], "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "card": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.tool.composition-tools", "version": 1, "value_sha256": "dfaffd1bb0d04d037b1f5b6d20868c8e797de297e4336a794566331291398f5f"}}, "related_packs": [{"pack_id": "checks-of-checks", "use": "Validate a proposed node's test cases before anyone relies on them."}, {"pack_id": "decomposition-patterns", "use": "Measure the baseline before changing anything when comparing recipe variants."}, {"pack_id": "tool-discovery", "use": "Trial another composition tool against this one with a comparable trial."}], "code_as_nouns": "The tested code lives in this pack's code folder as nouns, pinned by the folder digest that the manifest also lists. The library never runs it except in CI tests; a worker runs it under its own permissions, only from a checkout that passed verify-tools. Importing the pack runs nothing.", "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.runtime", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.catalog", "target_category": "noun.skill_pack", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.method", "target_category": "noun.skill_pack", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.ingest.csv-rows", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.clean.dedupe-by-key", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.clean.impute-numeric", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.clean.winsorize-outliers", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.feature.ratio-column", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.feature.rolling-zscore", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.text.normalize-whitespace", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.text.regex-extract", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.filter.threshold-gate", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.join.keyed-enrich", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.model.linear-risk-score", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.model.keyword-weighted-score", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.validate.schema-contract", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.validate.holdout-split", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.eval.binary-metrics", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.eval.shrinkage-select", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.agg.group-summary", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.format.markdown-report", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.recipe.ab-candidate-selection", "target_category": "noun.skill_pack", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.recipe.document-signal-digest", "target_category": "noun.skill_pack", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.recipe.tabular-anomaly-triage", "target_category": "noun.skill_pack", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.template.recipe-candidate", "target_category": "noun.skill_pack", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.template.compile-report", "target_category": "noun.eval_run", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.template.run-inputs", "target_category": "noun.benchmark_suite", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.template.run-receipt", "target_category": "noun.eval_run", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.template.verification-report", "target_category": "noun.eval_run", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.template.comparison", "target_category": "noun.eval_run", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.template.node-proposal", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.template.review-notes", "target_category": "noun.eval_run", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.example.prefix-reuse", "target_category": "noun.eval_run", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.tool.composition-tools", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:tool_card", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "tool_card", "pack": "code-composition", "pack_version": "0.2.0", "title": "Tool card: code composition tools", "category_reason": "A tool card pins the code's identity, license, interfaces and checks for the verbs that run it.", "name": "Code composition tools", "source": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs/tree/main/packs/code-composition/code", "tool_license": {"spdx": "MIT", "how_to_determine": "Read pyproject.toml in the code folder and the library's LICENSE."}, "pin": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}}, "pin_reason": "The code lives in this pack, so it is pinned by content, not by commit. Every digest in this pack was measured on the files that folder.sha256 covers. A code folder with another digest is a different tool until a new pack version pins it and verify-tools passes.", "folder_rule": "folder.sha256 is the library's pack-code digest: SHA-256 of `pack-code-v1` and a NUL byte, then the canonical JSON of the sorted [path, file SHA-256] pairs of every file under the code folder, skipping caches, virtual environments, build output and egg-info. The library build computes it from the files and the pack manifest repeats it, so a pin that no longer matches the code fails make check. To recompute it from a checkout's root: python3 -c \"import sys; sys.path.insert(0, 'scripts'); import build_packs as b; from pathlib import Path; print(b.code_digest(Path('packs/code-composition')))\"", "address_note": "Use a checkout of this library whose code folder matches folder.sha256. If none does, end blocked and say so; do not substitute another source. The folder digest is what must match.", "package_path_rule": "Module names in this pack, such as compiler.py, are relative to the import package that pyproject.toml lists under [tool.hatch.build.targets.wheel] packages.", "requires": {"python": ">=3.12", "dependencies": ["pydantic>=2.9", "httpx>=0.27"], "lockfile": "uv.lock in the code folder; install with uv sync --locked --all-groups there.", "tessera_for_integration": {"repository": "https://github.com/ta-amps/tessera-infrastructure-work-and-storage-engine", "commit": "55458514e84eaf1e524637c3bd04916ebb4b3c35", "install": "uv sync --locked --all-extras in that checkout"}}, "uses": ["Compile a declarative recipe into a checked graph of prewritten nodes (compiler.DeterministicCompiler.compile).", "Emit a standalone Python module for a compiled plan (compiler.DeterministicCompiler.emit_python_from_plan).", "Execute a compiled plan with a sub-graph cache and a SHA-256 receipt (runtime.DeterministicRuntime.execute).", "List, verify and register prewritten nodes in a SQLite node database (registry.NodeDatabase).", "Check one claimed seed task against its pins before running it (seed_worker.execute_seed_task).", "Export the code's own Tessera-shaped seed nouns and tasks as an offline preview document (seed_pack.build_seed_pack)."], "interfaces": {"python": ["compiler.DeterministicCompiler.compile", "compiler.DeterministicCompiler.emit_python_from_plan", "runtime.DeterministicRuntime.execute", "registry.NodeDatabase", "seed_worker.execute_seed_task"], "command_line": "The code-composition console script that pyproject.toml declares under [project.scripts], with subcommands init, nodes, verify-nodes, seed-pack, compile, run, compose and demo.", "make_targets": {"setup": "uv sync --locked --all-groups", "check": "ruff check, ruff format --check, mypy in strict mode and pytest", "demo": "verify all 18 nodes, compile and run the 3 recipes with the Python equivalence check, and show cached prefix reuse", "tessera-integration": "the seed export against Tessera's real models, with TESSERA_DIR set to a prepared Tessera checkout"}}, "checks": [{"command": "make check demo, in the code folder", "result_at_pin": "pass; pytest reports 41 passed and 2 skipped on Python 3.12.13 and 3.13.13 (the 2 Tessera tests skip without Tessera's environment)"}, {"command": "make tessera-integration TESSERA_DIR=<Tessera checkout at the commit above>, in the code folder", "result_at_pin": "pass; 2 passed"}, {"command": "make check, in the library", "result_at_pin": "pass; the build recomputes the folder digest from the files, and the code's own tests, run by its CI job, check the runtime, node and recipe pins against the code"}], "measured": "Measured on October 29, 2026 by the pack author in a library checkout on Linux, with Python 3.12.13 and 3.13.13 giving identical digests. A path-filtered CI job reruns these checks on every change to this pack. This is not independent verification.", "cautions": ["Run code only from a checkout whose code folder matches folder.sha256 and passed verify-tools. Never execute source code copied out of a noun.", "Node code and emitted Python run in the worker's own Python process; this is not a security sandbox.", "Every subcommand except seed-pack creates or migrates a SQLite file at its --db path, and without --db uses CODE_COMPOSITION_DB or a default path under the current directory; seed-pack opens an existing file read-only. Pass a path inside the task workspace.", "The compose subcommand calls a model endpoint when CODE_COMPOSITION_LLM_BASE_URL is set, and looks up earlier recipes in a Tessera deployment whenever TESSERA_URL is set, even with --offline. The verbs in this pack need neither; leave both unset.", "Seed export provenance reads the library checkout's HEAD only when the code sits at the pinned path; a copy anywhere else must pass --source-commit."], "install_policy": "This card installs nothing. A worker checks out the library, confirms the code folder's digest and installs its locked dependencies in its own task workspace under its execution policy.", "docs": ["https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs/blob/main/packs/code-composition/README.md", "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs/blob/main/packs/code-composition/code/README.md", "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs/blob/main/packs/code-composition/code/examples/recipes/README.md"], "used_by": ["code-composition.verify-tools", "code-composition.compose-recipe", "code-composition.compile-recipe", "code-composition.run-recipe", "code-composition.compare-runs", "code-composition.propose-node", "code-composition.review-node"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": []}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.runtime", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:runtime_manifest", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "runtime_manifest", "pack": "code-composition", "pack_version": "0.2.0", "title": "Compiler and runtime: entry points, checks and module digests of the pinned code", "category_reason": "Pins the exact compiler and runtime modules that every compile and run verb must use.", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}}, "entry_points": ["compiler.DeterministicCompiler.compile", "compiler.DeterministicCompiler.emit_python_from_plan", "runtime.DeterministicRuntime.execute"], "module_sha256": {"compiler.py": "481335073a73015822905bdd5033c72fca6d30571586af06b23fd4356d7fbcd0", "errors.py": "c35453098e6271a0800dda655d8cf1e93f40303417415e538dc00748e5e0a308", "public_limits.py": "a02d48edb97537eca6303e5948e19ff5aec8a30e3031b62038f00270e6c4c9df", "registry.py": "cee27cba94fcef1db9b2c5f9bd0e2f3a4f39a76a409433e2e6756e6a05e95d2d", "runtime.py": "0e4d8895a8e7dc45075249559c87936f47171676d654d34b5c59be546c33a25c", "schemas.py": "63b64f41774bf155d2c26bdcb484aeea733e6677999977931554e74db47b293a"}, "digest_rule": "SHA-256 of each module file's bytes with CRLF line endings normalized to LF. The code's seed_worker module applies the same rule before it runs a seed task, and the code's own tests check these pins in CI.", "compile_checks": ["Every step names a node in the node database; an unknown node id gets a close-match suggestion (node_not_found).", "Governance lens: the node's source matches its code_sha256, the node carries the code's own verified status tag and no quarantine tag, and its SPDX license is one of Apache-2.0, BSD-3-Clause, CC0-1.0, MIT (node_governance_failed).", "Parameters: unknown names are refused, int refuses booleans, numeric bounds and string choices are enforced, and a required parameter without a default must be set (parameter_constraint_failed).", "Edges: both ports exist, with a suggestion on a typo (port_not_found); source and destination port types are exactly equal (port_type_mismatch); an input port takes at most one edge (duplicate_input_wiring).", "Unwired inputs of root steps, and inputs listed in external_inputs as step.port, become graph entry inputs; an unwired required input on any other step is refused with its compatible upstream outputs (missing_required_input).", "Order: a deterministic Kahn topological sort in declaration order; a cycle is refused with its exact path (cycle_detected).", "Each step gets a Merkle fingerprint of its node digest, resolved parameters, entry ports and upstream fingerprints, so renaming steps does not change it and any upstream change does.", "Warnings, not errors: isolated_step and dangling_transform."], "runtime_behavior": ["Zero model calls; every receipt records llm_tokens_at_runtime 0.", "A step's cached output is reused when its fingerprint and input digest match; cached and fresh outputs are both checked against the declared port types.", "Entry inputs are matched by port name, or by step.port when a port name appears on more than one root step; a missing or wrongly typed entry input is refused (execution_input_invalid).", "Receipts carry recipe, plan, node, input and output digests, the executed and cached steps, and a receipt digest.", "With the equivalence check on, the emitted standalone module runs on the same inputs and must give byte-identical step and terminal outputs."], "trust_note": "Execution is in-process and trusts the verified nodes. It is not a sandbox for unreviewed code.", "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.catalog", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.skill_pack", "pack:code-composition", "role:catalog", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.skill_pack", "role": "catalog", "pack": "code-composition", "pack_version": "0.2.0", "title": "Node catalog: 18 prewritten nodes, their signatures and port types", "category_reason": "The catalog is the vocabulary a recipe may use: tool bindings with typed signatures.", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}}, "port_types": {"records": "a list of objects", "table": "an object", "series": "a list of finite numbers", "text": "a string", "json": "an object or a list", "metrics": "an object", "artifact": "a string, such as a rendered report"}, "param_types": {"int": "an integer; booleans are refused", "float": "a number", "str": "a string, optionally limited to listed choices", "bool": "true or false", "str_list": "a list of strings"}, "edge_rule": "An edge connects an output port to an input port of exactly the same port type.", "signature_notation": "node_id(input:type, optional_input:type?) [param:type, param:type=default] -> (output:type) # summary. A parameter shown as name:type=<set in code> has a default that this pack does not repeat; pass it explicitly. Signature lines print defaults as the code does; the node nouns' parameter lists write whole-number defaults as integers, as Tessera stores them.", "code_digest_rule": "A node's code_sha256 is the SHA-256 of its source after CRLF is normalized to LF, trailing spaces are removed from each line, surrounding blank lines are stripped and one final newline is added (schemas.compute_code_sha256).", "signatures": ["ingest.csv_rows(raw_csv:text) [delimiter:str=\",\", strip_values:bool=true] -> (rows:records, ingest_stats:metrics) # Parse delimiter-separated text into typed row records with numeric coercion.", "clean.dedupe_by_key(rows:records) [key_field:str, keep:str=\"first\"] -> (rows:records, dedupe_stats:metrics) # Deduplicate row records by a key column while keeping the first or last occurrence.", "clean.impute_numeric(rows:records) [fields:str_list, strategy:str=\"median\", fill_value:float=0.0] -> (rows:records, impute_stats:metrics) # Fill missing numeric fields across records using median, mean, or constant fallback.", "clean.winsorize_outliers(rows:records) [field:str, lower_q:float=0.05, upper_q:float=0.95] -> (rows:records, clamp_stats:metrics) # Clamp extreme numeric values in a field to empirical lower and upper quantiles.", "feature.ratio_column(rows:records) [numerator:str, denominator:str, output_field:str=\"ratio\", epsilon:float=1e-09] -> (rows:records, values:series) # Compute a safe numerator-over-denominator ratio column across row records.", "feature.rolling_zscore(rows:records) [field:str, output_field:str=\"zscore\", window:int=5] -> (rows:records, zscores:series) # Compute trailing-window z-scores over a numeric record field.", "text.normalize_whitespace(raw_text:text) [lowercase:bool=false, collapse_blank_lines:bool=true] -> (clean_text:text, text_stats:metrics) # Collapse horizontal whitespace, trim lines, and optionally lowercase raw text.", "text.regex_extract(clean_text:text) [pattern:str, record_prefix:str=\"doc\"] -> (rows:records, extract_stats:metrics) # Extract structured row records from normalized text via a regular expression.", "filter.threshold_gate(rows:records) [field:str, op:str=\"gte\", threshold:float=0.5] -> (passed:records, rejected:records, gate_stats:metrics) # Partition records into passing and rejected subsets using a numeric threshold rule.", "join.keyed_enrich(left_rows:records, right_rows:records) [key_field:str, how:str=\"left\", right_prefix:str=\"\"] -> (rows:records, join_stats:metrics) # Join primary records with lookup enrichment records on a shared key column.", "model.linear_risk_score(rows:records) [feature_fields:str_list, weights_csv:str=\"1.0\", bias:float=0.0, output_field:str=\"risk_score\"] -> (rows:records, scores:series) # Compute a calibrated logistic risk score from weighted numeric features and bias.", "model.keyword_weighted_score(rows:records) [text_field:str=\"message\", keywords:str_list, scale:float=3.0, output_field:str=\"signal_score\"] -> (rows:records, scores:series) # Score record text fields by case-insensitive keyword occurrences normalized to [0, 1].", "validate.schema_contract(rows:records) [required_fields:str_list, min_rows:int=1, strict:bool=true] -> (rows:records, contract_report:metrics) # Verify minimum row count and required column presence before downstream steps.", "validate.holdout_split(rows:records) [key_field:str, holdout_fraction:float=0.35, salt:str=<set in code>] -> (train_rows:records, holdout_rows:records, split_stats:metrics) # Deterministically hash-split records into calibration and holdout partitions by key.", "eval.binary_metrics(rows:records) [score_field:str=\"risk_score\", label_field:str=\"label\", threshold:float=0.5] -> (eval_metrics:metrics) # Compute precision, recall, F1, accuracy, and Brier score against binary ground-truth labels.", "eval.shrinkage_select(candidate_a:metrics, candidate_b:metrics) [metric_key:str=\"f1\", count_key:str=\"sample_count\", prior_mean:float=0.5, prior_strength:float=8.0, min_margin:float=0.01] -> (selection:json, winner_metrics:metrics) # Compare two candidate metric bundles using empirical-Bayes shrinkage toward a conservative prior.", "agg.group_summary(rows:records) [group_field:str, value_field:str] -> (summary_table:table, agg_stats:metrics) # Aggregate records by a categorical key into count, sum, mean, and max table rows.", "format.markdown_report(summary_table:table, headline_metrics:metrics, extra_context:json?) [title:str=\"Pipeline Report\", max_rows:int=20] -> (report_md:artifact, digest_line:text) # Render a deterministic Markdown report artifact from a summary table and headline metrics."], "nodes": [{"node_id": "ingest.csv_rows", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.ingest.csv-rows", "version": 1, "value_sha256": "8d4c5d6bd57d96f13fc15d64ad0684853f6d824dd7f3a145da83b411834224fc"}}, {"node_id": "clean.dedupe_by_key", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.clean.dedupe-by-key", "version": 1, "value_sha256": "0e3459f4cdd87acb631eb1df1baf53a8fa0b42bc473537b638de3a0fba147fb4"}}, {"node_id": "clean.impute_numeric", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.clean.impute-numeric", "version": 1, "value_sha256": "8237f2cfe20100ce496b982b688043539837fb0a4814513b85272aa722c91610"}}, {"node_id": "clean.winsorize_outliers", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.clean.winsorize-outliers", "version": 1, "value_sha256": "46b5ecc1c4cef93cae1cbdb55c0222f20d337a7bb687b6f89d3e5ff7b01ae517"}}, {"node_id": "feature.ratio_column", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.feature.ratio-column", "version": 1, "value_sha256": "c50f0ec317ee05a1ffa9658b3e6065d6b5f73dede3d401f24320febd7f8b2705"}}, {"node_id": "feature.rolling_zscore", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.feature.rolling-zscore", "version": 1, "value_sha256": "678abdbae976e170a754ce21f6e92eaa7c7bc5e031bf9829cc142d03f29f3922"}}, {"node_id": "text.normalize_whitespace", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.text.normalize-whitespace", "version": 1, "value_sha256": "856f031d30e4bd03f369b827cfdf08c345f7daf0be98a1f31b5d1bdfdb82a8e9"}}, {"node_id": "text.regex_extract", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.text.regex-extract", "version": 1, "value_sha256": "88858da082102b84638f3037e2012ac9a8a9abac1abde6b06f9dfdbdabd77893"}}, {"node_id": "filter.threshold_gate", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.filter.threshold-gate", "version": 1, "value_sha256": "498b48699ff70d42f2c5cb12856eba8d8898b5d951d9f95e687991da7f3daca9"}}, {"node_id": "join.keyed_enrich", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.join.keyed-enrich", "version": 1, "value_sha256": "59cac8872adc13dff45703f12459fe7baf2094a298dc13db42b47809d627564c"}}, {"node_id": "model.linear_risk_score", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.model.linear-risk-score", "version": 1, "value_sha256": "7dc869e317c750aebace2cbdb947fef44528cb3c5b71cc6b38fcb6383c2f6486"}}, {"node_id": "model.keyword_weighted_score", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.model.keyword-weighted-score", "version": 1, "value_sha256": "6129dfb30b29984a7d64e13f3e1eb93eb4a2aa7e4a0bf442776584aa3166d5ad"}}, {"node_id": "validate.schema_contract", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.validate.schema-contract", "version": 1, "value_sha256": "18943311608bbea97b67eb69da2d8abb8d685f664dc31108e52796e08919f47e"}}, {"node_id": "validate.holdout_split", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.validate.holdout-split", "version": 1, "value_sha256": "884c55bc3e5fdd5f1bb5ce0650ea0bb706c0e4849f0e492ce00d2b9cd06e45f0"}}, {"node_id": "eval.binary_metrics", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.eval.binary-metrics", "version": 1, "value_sha256": "060eff11d7374ea0f0362ea0dd894bca041d009e9729ed4e08b3cc147216c20d"}}, {"node_id": "eval.shrinkage_select", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.eval.shrinkage-select", "version": 1, "value_sha256": "7a710e73abca23c201de5eccaa5400b0ae3b7571ef41440cacacc70f31ec4870"}}, {"node_id": "agg.group_summary", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.agg.group-summary", "version": 1, "value_sha256": "d3afae7525a89c5d0768446224e46958f06a1bcc4a2b644a6fd88232f50f9af7"}}, {"node_id": "format.markdown_report", "pin": {"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.format.markdown-report", "version": 1, "value_sha256": "510b86a1970011ce8e0492ccb2e26f64ee6bb8bf6e046624fad45a8f3466261e"}}], "node_categories": {"ingest": ["ingest.csv_rows"], "clean": ["clean.dedupe_by_key", "clean.impute_numeric", "clean.winsorize_outliers"], "feature": ["feature.ratio_column", "feature.rolling_zscore"], "text": ["text.normalize_whitespace", "text.regex_extract"], "filter": ["filter.threshold_gate"], "join": ["join.keyed_enrich"], "model": ["model.linear_risk_score", "model.keyword_weighted_score"], "validate": ["validate.schema_contract", "validate.holdout_split"], "eval": ["eval.binary_metrics", "eval.shrinkage_select"], "agg": ["agg.group_summary"], "format": ["format.markdown_report"]}, "token_estimate_at_pin": {"signature_chars": 4316, "raw_source_chars": 22476, "signature_tokens_est": 1079, "raw_source_tokens_est": 5619, "method": "The code's own catalog statistics with the pinned code; tokens are estimated as characters divided by 4."}, "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.runtime", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.ingest.csv-rows", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.clean.dedupe-by-key", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.clean.impute-numeric", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.clean.winsorize-outliers", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.feature.ratio-column", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.feature.rolling-zscore", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.text.normalize-whitespace", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.text.regex-extract", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.filter.threshold-gate", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.join.keyed-enrich", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.model.linear-risk-score", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.model.keyword-weighted-score", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.validate.schema-contract", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.validate.holdout-split", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.eval.binary-metrics", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.eval.shrinkage-select", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.agg.group-summary", "target_category": "noun.code_node", "note": ""}, {"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.node.format.markdown-report", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.method", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.skill_pack", "pack:code-composition", "role:method", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.skill_pack", "role": "method", "pack": "code-composition", "pack_version": "0.2.0", "title": "How to compose verified code without rewriting it", "category_reason": "A reusable method with its guardrails.", "principles": ["Compose instead of rewriting: a recipe names catalog node ids, wires their ports with edges and sets bounded parameters. It contains no code.", "Read signatures, not source: the catalog's one-line signatures are enough to write a recipe.", "Compile before running. The compiler refuses unknown nodes, wrong port types, bad parameters, missing wiring and cycles with a typed error code, the step, the port and often a suggestion.", "Repair from diagnostics: change the step, port or parameter the compiler names. Never work around a refusal by writing code into a recipe or a node.", "Run only pinned, verified code: a checkout whose code folder matches the tool card's folder digest and passed verify-tools. Never execute source code copied out of a noun.", "Runs make no model calls, and every receipt shows it.", "Pin everything: tool folder digest, node digests, recipe digest and input digest. A change to any of them is a new run, not an update to an old receipt.", "Change one thing at a time. A variant that keeps upstream steps unchanged reuses their cached outputs, so the comparison is cheap and its differences are attributable.", "Grow the catalog deliberately. When no node fits, propose one with exact-value tests; a different worker or a person reviews it, and adding it to the pack's code is the owner's decision."], "repair_codes": {"node_not_found": "Use a catalog node id; the diagnostic suggests the closest one.", "parameter_constraint_failed": "Fix the parameter's name, type, bounds or choice.", "port_not_found": "Use one of the ports the diagnostic lists.", "port_type_mismatch": "Wire a port of exactly the same type, or insert a node that converts it.", "missing_required_input": "Wire one of the compatible upstream outputs the diagnostic lists.", "duplicate_input_wiring": "Keep one edge per input port.", "cycle_detected": "Break the reported cycle path.", "unknown_step": "Make every edge name declared steps.", "duplicate_step_id": "Give every step a unique id.", "invalid_external_input": "Write external inputs as step.port for a declared step and port.", "conflicting_external_input": "Do not list a wired port as an external input.", "empty_recipe": "Declare at least one step.", "node_governance_failed": "Stop: the node fails the governance lens and must not be used.", "execution_input_invalid": "At run time: supply every entry input with its declared port type, using step.port when a port name is ambiguous."}, "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": []}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.ingest.csv-rows", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: ingest.csv_rows", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "ingest.csv_rows", "node_version": "1.0.0", "node_category": "ingest", "summary": "Parse delimiter-separated text into typed row records with numeric coercion.", "signature": "ingest.csv_rows(raw_csv:text) [delimiter:str=\",\", strip_values:bool=true] -> (rows:records, ingest_stats:metrics) # Parse delimiter-separated text into typed row records with numeric coercion.", "inputs": [{"name": "raw_csv", "port_type": "text", "required": true, "description": "Headered delimiter-separated text payload."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Parsed list of typed dictionary records."}, {"name": "ingest_stats", "port_type": "metrics", "description": "Row and column counts parsed from CSV text."}], "params": [{"name": "delimiter", "param_type": "str", "required": false, "default": ",", "choices": [",", "\t", "|", ";"], "description": "Field delimiter character."}, {"name": "strip_values", "param_type": "bool", "required": false, "default": true, "description": "Trim whitespace around cell strings and headers."}], "function_name": "node_ingest_csv_rows", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "8f6a01cec2e2c7514e0b578b58b2ec4c5b9fbd9786c35cd0d6e4fed6534dcf20", "source_lines": 37}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["coerces_numbers_and_nulls"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection", "tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.clean.dedupe-by-key", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: clean.dedupe_by_key", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "clean.dedupe_by_key", "node_version": "1.0.0", "node_category": "clean", "summary": "Deduplicate row records by a key column while keeping the first or last occurrence.", "signature": "clean.dedupe_by_key(rows:records) [key_field:str, keep:str=\"first\"] -> (rows:records, dedupe_stats:metrics) # Deduplicate row records by a key column while keeping the first or last occurrence.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Input row records that may contain duplicate keys."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Deduplicated row records in deterministic order."}, {"name": "dedupe_stats", "port_type": "metrics", "description": "Input, unique, and duplicate removal counts."}], "params": [{"name": "key_field", "param_type": "str", "required": true, "description": "Record field used as deduplication key."}, {"name": "keep", "param_type": "str", "required": false, "default": "first", "choices": ["first", "last"], "description": "Keep first or last record per duplicate key."}], "function_name": "node_clean_dedupe_by_key", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "ce12ccb08e0b6aa4e3576dba816f43df875758e68c1be5a49741a1acf5eed74e", "source_lines": 27}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["dedupe_first_and_counts"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection", "document-signal-digest", "tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.clean.impute-numeric", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: clean.impute_numeric", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "clean.impute_numeric", "node_version": "1.0.0", "node_category": "clean", "summary": "Fill missing numeric fields across records using median, mean, or constant fallback.", "signature": "clean.impute_numeric(rows:records) [fields:str_list, strategy:str=\"median\", fill_value:float=0.0] -> (rows:records, impute_stats:metrics) # Fill missing numeric fields across records using median, mean, or constant fallback.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Input records with potential null numeric cells."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Records with missing numeric fields imputed."}, {"name": "impute_stats", "port_type": "metrics", "description": "Imputed cell count and field count."}], "params": [{"name": "fields", "param_type": "str_list", "required": true, "description": "List of numeric field names to impute."}, {"name": "strategy", "param_type": "str", "required": false, "default": "median", "choices": ["median", "mean", "constant"], "description": "Statistic used to compute fill values."}, {"name": "fill_value", "param_type": "float", "required": false, "default": 0, "description": "Fallback constant when strategy is constant or column is all-null."}], "function_name": "node_clean_impute_numeric", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "558f7cbc0d6428bebea826dd02539328efbd36d0f7c674b2535d9d09a5a50d6f", "source_lines": 40}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["median_imputation"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection", "tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.clean.winsorize-outliers", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: clean.winsorize_outliers", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "clean.winsorize_outliers", "node_version": "1.0.0", "node_category": "clean", "summary": "Clamp extreme numeric values in a field to empirical lower and upper quantiles.", "signature": "clean.winsorize_outliers(rows:records) [field:str, lower_q:float=0.05, upper_q:float=0.95] -> (rows:records, clamp_stats:metrics) # Clamp extreme numeric values in a field to empirical lower and upper quantiles.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Input records containing the numeric target field."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Records with target field clamped to quantile bounds."}, {"name": "clamp_stats", "port_type": "metrics", "description": "Clamped cell count plus lower and upper bounds."}], "params": [{"name": "field", "param_type": "str", "required": true, "description": "Numeric field name to winsorize."}, {"name": "lower_q", "param_type": "float", "required": false, "default": 0.05, "min_value": 0, "max_value": 0.49, "description": "Lower quantile in [0.0, 0.49]."}, {"name": "upper_q", "param_type": "float", "required": false, "default": 0.95, "min_value": 0.51, "max_value": 1, "description": "Upper quantile in [0.51, 1.0]."}], "function_name": "node_clean_winsorize_outliers", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "d2c65e712754e091f70d8833e2a36000442204402171336b50938c3258a3343d", "source_lines": 49}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["clamps_high_spike"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.feature.ratio-column", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: feature.ratio_column", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "feature.ratio_column", "node_version": "1.0.0", "node_category": "feature", "summary": "Compute a safe numerator-over-denominator ratio column across row records.", "signature": "feature.ratio_column(rows:records) [numerator:str, denominator:str, output_field:str=\"ratio\", epsilon:float=1e-09] -> (rows:records, values:series) # Compute a safe numerator-over-denominator ratio column across row records.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Input records containing numerator and denominator columns."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Records augmented with the computed ratio field."}, {"name": "values", "port_type": "series", "description": "Ordered numeric ratio series across rows."}], "params": [{"name": "numerator", "param_type": "str", "required": true, "description": "Numerator field name."}, {"name": "denominator", "param_type": "str", "required": true, "description": "Denominator field name."}, {"name": "output_field", "param_type": "str", "required": false, "default": "ratio", "description": "Destination field name written onto each record."}, {"name": "epsilon", "param_type": "float", "required": false, "default": 1e-09, "min_value": 1e-12, "max_value": 1, "description": "Zero-division floor applied when denominator magnitude is tiny."}], "function_name": "node_feature_ratio_column", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "7623a86d7f774a0da83f23dc62413325cbaa4a2a627a2f3838877a03e8e05c15", "source_lines": 20}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["computes_error_rate"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection", "tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.feature.rolling-zscore", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: feature.rolling_zscore", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "feature.rolling_zscore", "node_version": "1.0.0", "node_category": "feature", "summary": "Compute trailing-window z-scores over a numeric record field.", "signature": "feature.rolling_zscore(rows:records) [field:str, output_field:str=\"zscore\", window:int=5] -> (rows:records, zscores:series) # Compute trailing-window z-scores over a numeric record field.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Ordered input records containing the numeric target field."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Records augmented with trailing z-score values."}, {"name": "zscores", "port_type": "series", "description": "Ordered numeric z-score series."}], "params": [{"name": "field", "param_type": "str", "required": true, "description": "Numeric field name to standardize."}, {"name": "output_field", "param_type": "str", "required": false, "default": "zscore", "description": "Destination z-score field name."}, {"name": "window", "param_type": "int", "required": false, "default": 5, "min_value": 2, "max_value": 500, "description": "Trailing window size (>= 2)."}], "function_name": "node_feature_rolling_zscore", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "7d78a7bf2559b0abb9dae2a00102a604c0203f064a87ab6e879ad6a196ed90e5", "source_lines": 25}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["trailing_spike_positive_zscore"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.text.normalize-whitespace", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: text.normalize_whitespace", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "text.normalize_whitespace", "node_version": "1.0.0", "node_category": "text", "summary": "Collapse horizontal whitespace, trim lines, and optionally lowercase raw text.", "signature": "text.normalize_whitespace(raw_text:text) [lowercase:bool=false, collapse_blank_lines:bool=true] -> (clean_text:text, text_stats:metrics) # Collapse horizontal whitespace, trim lines, and optionally lowercase raw text.", "inputs": [{"name": "raw_text", "port_type": "text", "required": true, "description": "Unstructured multi-line text document or log stream."}], "outputs": [{"name": "clean_text", "port_type": "text", "description": "Whitespace-normalized text."}, {"name": "text_stats", "port_type": "metrics", "description": "Character, line, and word counts after normalization."}], "params": [{"name": "lowercase", "param_type": "bool", "required": false, "default": false, "description": "Convert text to lowercase when true."}, {"name": "collapse_blank_lines", "param_type": "bool", "required": false, "default": true, "description": "Drop empty lines when true."}], "function_name": "node_text_normalize_whitespace", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "d734197b1bd36e19863b2b32e296c660568c8520e491796f003b5457138afd74", "source_lines": 27}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["collapses_tabs_and_blanks"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["document-signal-digest"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.text.regex-extract", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: text.regex_extract", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "text.regex_extract", "node_version": "1.0.0", "node_category": "text", "summary": "Extract structured row records from normalized text via a regular expression.", "signature": "text.regex_extract(clean_text:text) [pattern:str, record_prefix:str=\"doc\"] -> (rows:records, extract_stats:metrics) # Extract structured row records from normalized text via a regular expression.", "inputs": [{"name": "clean_text", "port_type": "text", "required": true, "description": "Normalized text input scanned line-by-line or multi-line."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Extracted structured records with named regex groups."}, {"name": "extract_stats", "port_type": "metrics", "description": "Total regex matches extracted."}], "params": [{"name": "pattern", "param_type": "str", "required": true, "description": "Regular expression with named capture groups."}, {"name": "record_prefix", "param_type": "str", "required": false, "default": "doc", "description": "Fallback ID prefix when pattern omits doc_id."}], "function_name": "node_text_regex_extract", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "574f723411a467c47213744ec8dba97674fe042a797bb8fa46db09e1468f3c7c", "source_lines": 29}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["extracts_named_incident_lines"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["document-signal-digest"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.filter.threshold-gate", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: filter.threshold_gate", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "filter.threshold_gate", "node_version": "1.0.0", "node_category": "filter", "summary": "Partition records into passing and rejected subsets using a numeric threshold rule.", "signature": "filter.threshold_gate(rows:records) [field:str, op:str=\"gte\", threshold:float=0.5] -> (passed:records, rejected:records, gate_stats:metrics) # Partition records into passing and rejected subsets using a numeric threshold rule.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Input records evaluated against the numeric threshold."}], "outputs": [{"name": "passed", "port_type": "records", "description": "Records satisfying the comparison operator and threshold."}, {"name": "rejected", "port_type": "records", "description": "Records failing the comparison operator and threshold."}, {"name": "gate_stats", "port_type": "metrics", "description": "Counts and pass rate across evaluated records."}], "params": [{"name": "field", "param_type": "str", "required": true, "description": "Numeric field compared against threshold."}, {"name": "op", "param_type": "str", "required": false, "default": "gte", "choices": ["gt", "gte", "lt", "lte", "eq"], "description": "Comparison operator."}, {"name": "threshold", "param_type": "float", "required": false, "default": 0.5, "description": "Decision threshold value."}], "function_name": "node_filter_threshold_gate", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "dd4bdce30f000d468f32f9ac9b42ddb4dbebf9cb2264fd3645bf45f3a9971d7a", "source_lines": 35}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["splits_high_risk_records"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["document-signal-digest", "tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.join.keyed-enrich", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: join.keyed_enrich", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "join.keyed_enrich", "node_version": "1.0.0", "node_category": "join", "summary": "Join primary records with lookup enrichment records on a shared key column.", "signature": "join.keyed_enrich(left_rows:records, right_rows:records) [key_field:str, how:str=\"left\", right_prefix:str=\"\"] -> (rows:records, join_stats:metrics) # Join primary records with lookup enrichment records on a shared key column.", "inputs": [{"name": "left_rows", "port_type": "records", "required": true, "description": "Primary left-hand records."}, {"name": "right_rows", "port_type": "records", "required": true, "description": "Lookup enrichment records indexed by key_field."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Joined and enriched records."}, {"name": "join_stats", "port_type": "metrics", "description": "Left, matched, and output record counts."}], "params": [{"name": "key_field", "param_type": "str", "required": true, "description": "Shared join key column."}, {"name": "how", "param_type": "str", "required": false, "default": "left", "choices": ["left", "inner"], "description": "Join strategy (left keeps unmatched left records; inner drops them)."}, {"name": "right_prefix", "param_type": "str", "required": false, "default": "", "description": "Optional prefix added to non-key right-hand columns."}], "function_name": "node_join_keyed_enrich", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "407c9086f2cf17d5de483e220a330ffc995187cb0efdf64e55c041b064522072", "source_lines": 40}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["left_joins_owner_metadata"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.model.linear-risk-score", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: model.linear_risk_score", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "model.linear_risk_score", "node_version": "1.0.0", "node_category": "model", "summary": "Compute a calibrated logistic risk score from weighted numeric features and bias.", "signature": "model.linear_risk_score(rows:records) [feature_fields:str_list, weights_csv:str=\"1.0\", bias:float=0.0, output_field:str=\"risk_score\"] -> (rows:records, scores:series) # Compute a calibrated logistic risk score from weighted numeric features and bias.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Feature-engineered input records."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Records augmented with bounded [0, 1] logistic score."}, {"name": "scores", "port_type": "series", "description": "Ordered logistic probability series."}], "params": [{"name": "feature_fields", "param_type": "str_list", "required": true, "description": "Ordered list of numeric feature column names."}, {"name": "weights_csv", "param_type": "str", "required": false, "default": "1.0", "description": "Comma-separated float weights aligned to feature_fields."}, {"name": "bias", "param_type": "float", "required": false, "default": 0, "min_value": -20, "max_value": 20, "description": "Additive intercept prior to logistic link."}, {"name": "output_field", "param_type": "str", "required": false, "default": "risk_score", "description": "Destination score column name."}], "function_name": "node_model_linear_risk_score", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "cdc2934bb2c7d9779ad4d4ce38d63e9b3cfd964488c4ff0a48a53768298fd266", "source_lines": 34}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["zero_logit_is_half"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection", "tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.model.keyword-weighted-score", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: model.keyword_weighted_score", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "model.keyword_weighted_score", "node_version": "1.0.0", "node_category": "model", "summary": "Score record text fields by case-insensitive keyword occurrences normalized to [0, 1].", "signature": "model.keyword_weighted_score(rows:records) [text_field:str=\"message\", keywords:str_list, scale:float=3.0, output_field:str=\"signal_score\"] -> (rows:records, scores:series) # Score record text fields by case-insensitive keyword occurrences normalized to [0, 1].", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Records containing a text column to scan."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Records augmented with normalized keyword score and matched terms."}, {"name": "scores", "port_type": "series", "description": "Ordered keyword signal scores in [0.0, 1.0]."}], "params": [{"name": "text_field", "param_type": "str", "required": false, "default": "message", "description": "Text column name on each record."}, {"name": "keywords", "param_type": "str_list", "required": true, "description": "Case-insensitive signal terms to match."}, {"name": "scale", "param_type": "float", "required": false, "default": 3, "min_value": 0.5, "max_value": 50, "description": "Hit count denominator for saturation at 1.0."}, {"name": "output_field", "param_type": "str", "required": false, "default": "signal_score", "description": "Destination score column name."}], "function_name": "node_model_keyword_weighted_score", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "22274b95aad1180c92d79c16e5581eb4bbf421d164d8c22abd95d73bb590dc4b", "source_lines": 20}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["scores_incident_keywords"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["document-signal-digest"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.validate.schema-contract", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: validate.schema_contract", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "validate.schema_contract", "node_version": "1.0.0", "node_category": "validate", "summary": "Verify minimum row count and required column presence before downstream steps.", "signature": "validate.schema_contract(rows:records) [required_fields:str_list, min_rows:int=1, strict:bool=true] -> (rows:records, contract_report:metrics) # Verify minimum row count and required column presence before downstream steps.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Input records checked against structural contract."}], "outputs": [{"name": "rows", "port_type": "records", "description": "Validated records containing all required column keys."}, {"name": "contract_report", "port_type": "metrics", "description": "Validation summary counts."}], "params": [{"name": "required_fields", "param_type": "str_list", "required": true, "description": "Column keys that must exist on every record."}, {"name": "min_rows", "param_type": "int", "required": false, "default": 1, "min_value": 0, "max_value": 100000, "description": "Minimum acceptable record count."}, {"name": "strict", "param_type": "bool", "required": false, "default": true, "description": "Raise ValueError when contract violations occur."}], "function_name": "node_validate_schema_contract", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "ce23196d7a1eb6149c5d01da62c52332ab0d428ee8326e3eb764ed7abe13d7c4", "source_lines": 33}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["passes_complete_schema"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.validate.holdout-split", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: validate.holdout_split", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "validate.holdout_split", "node_version": "1.0.0", "node_category": "validate", "summary": "Deterministically hash-split records into calibration and holdout partitions by key.", "signature": "validate.holdout_split(rows:records) [key_field:str, holdout_fraction:float=0.35, salt:str=<set in code>] -> (train_rows:records, holdout_rows:records, split_stats:metrics) # Deterministically hash-split records into calibration and holdout partitions by key.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Input records partitioned deterministically by SHA-256 hash."}], "outputs": [{"name": "train_rows", "port_type": "records", "description": "Calibration partition records."}, {"name": "holdout_rows", "port_type": "records", "description": "Leak-free holdout partition records."}, {"name": "split_stats", "port_type": "metrics", "description": "Partition sizes and empirical holdout ratio."}], "params": [{"name": "key_field", "param_type": "str", "required": true, "description": "Entity key hashed so identical keys never straddle train and holdout."}, {"name": "holdout_fraction", "param_type": "float", "required": false, "default": 0.35, "min_value": 0.05, "max_value": 0.95, "description": "Target fraction routed into holdout_rows."}, {"name": "salt", "param_type": "str", "required": false, "default_set_in_code": true, "description": "Hash salt for reproducible partition seeds. The pinned code sets a fixed default string; pass salt explicitly, as the bundled A/B recipe does with ab-eval-v1."}], "function_name": "node_validate_holdout_split", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "6f2e82304825ed01c41e0bf676f053cee928c1e8ea7085b99c6cd64362e5e7e2", "source_lines": 36}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["deterministic_non_empty_partitions"], "with_exact_expected_values": 0, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.eval.binary-metrics", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: eval.binary_metrics", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "eval.binary_metrics", "node_version": "1.0.0", "node_category": "eval", "summary": "Compute precision, recall, F1, accuracy, and Brier score against binary ground-truth labels.", "signature": "eval.binary_metrics(rows:records) [score_field:str=\"risk_score\", label_field:str=\"label\", threshold:float=0.5] -> (eval_metrics:metrics) # Compute precision, recall, F1, accuracy, and Brier score against binary ground-truth labels.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Scored records containing continuous predictions and binary 0/1 labels."}], "outputs": [{"name": "eval_metrics", "port_type": "metrics", "description": "Classification and calibration metrics on the evaluated split."}], "params": [{"name": "score_field", "param_type": "str", "required": false, "default": "risk_score", "description": "Predicted probability field in [0, 1]."}, {"name": "label_field", "param_type": "str", "required": false, "default": "label", "description": "Ground-truth binary label field (1 or 0)."}, {"name": "threshold", "param_type": "float", "required": false, "default": 0.5, "min_value": 0, "max_value": 1, "description": "Classification cutoff applied to score_field."}], "function_name": "node_eval_binary_metrics", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "2fe1605b34f6b9a739274c476b55707c456cd558a8aeb4001582969397c0cd94", "source_lines": 48}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["perfect_binary_predictions"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.eval.shrinkage-select", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: eval.shrinkage_select", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "eval.shrinkage_select", "node_version": "1.0.0", "node_category": "eval", "summary": "Compare two candidate metric bundles using empirical-Bayes shrinkage toward a conservative prior.", "signature": "eval.shrinkage_select(candidate_a:metrics, candidate_b:metrics) [metric_key:str=\"f1\", count_key:str=\"sample_count\", prior_mean:float=0.5, prior_strength:float=8.0, min_margin:float=0.01] -> (selection:json, winner_metrics:metrics) # Compare two candidate metric bundles using empirical-Bayes shrinkage toward a conservative prior.", "inputs": [{"name": "candidate_a", "port_type": "metrics", "required": true, "description": "Baseline arm evaluation metrics."}, {"name": "candidate_b", "port_type": "metrics", "required": true, "description": "Challenger arm evaluation metrics."}], "outputs": [{"name": "selection", "port_type": "json", "description": "Structured decision record with raw and shrunk scores."}, {"name": "winner_metrics", "port_type": "metrics", "description": "Winning arm metrics augmented with shrunk lift."}], "params": [{"name": "metric_key", "param_type": "str", "required": false, "default": "f1", "description": "Metric key maximized during arm comparison."}, {"name": "count_key", "param_type": "str", "required": false, "default": "sample_count", "description": "Sample count key weighting empirical observations against prior_strength."}, {"name": "prior_mean", "param_type": "float", "required": false, "default": 0.5, "min_value": 0, "max_value": 1, "description": "Conservative prior mean for small-sample shrinkage."}, {"name": "prior_strength", "param_type": "float", "required": false, "default": 8, "min_value": 0, "max_value": 1000, "description": "Effective pseudo-sample weight on prior_mean."}, {"name": "min_margin", "param_type": "float", "required": false, "default": 0.01, "min_value": 0, "max_value": 0.5, "description": "Minimum shrunk gain required for candidate_b to beat baseline candidate_a."}], "function_name": "node_eval_shrinkage_select", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "584854abcc0623604c6c6c29549bf00eb529774178911ce43ebb23700acaedb0", "source_lines": 47}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["promotes_challenger_above_shrunk_margin"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.agg.group-summary", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: agg.group_summary", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "agg.group_summary", "node_version": "1.0.0", "node_category": "agg", "summary": "Aggregate records by a categorical key into count, sum, mean, and max table rows.", "signature": "agg.group_summary(rows:records) [group_field:str, value_field:str] -> (summary_table:table, agg_stats:metrics) # Aggregate records by a categorical key into count, sum, mean, and max table rows.", "inputs": [{"name": "rows", "port_type": "records", "required": true, "description": "Records grouped by group_field and aggregated over value_field."}], "outputs": [{"name": "summary_table", "port_type": "table", "description": "Tabular summary with columns and deterministically ordered rows."}, {"name": "agg_stats", "port_type": "metrics", "description": "Group count and total aggregated records."}], "params": [{"name": "group_field", "param_type": "str", "required": true, "description": "Categorical grouping column name."}, {"name": "value_field", "param_type": "str", "required": true, "description": "Numeric value column aggregated per group."}], "function_name": "node_agg_group_summary", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "f7043f84a8805e035ecfb94590c3a14dbd5fdb93ba053a8b945ea7619dec8da6", "source_lines": 32}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["groups_and_sorts_by_mean_desc"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection", "document-signal-digest", "tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.node.format.markdown-report", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.code_node", "pack:code-composition", "role:prewritten_node", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.code_node", "role": "prewritten_node", "pack": "code-composition", "pack_version": "0.2.0", "title": "Prewritten node: format.markdown_report", "category_reason": "A prewritten node is a pure Python function with a typed contract, pinned by its source digest.", "node_id": "format.markdown_report", "node_version": "1.0.0", "node_category": "format", "summary": "Render a deterministic Markdown report artifact from a summary table and headline metrics.", "signature": "format.markdown_report(summary_table:table, headline_metrics:metrics, extra_context:json?) [title:str=\"Pipeline Report\", max_rows:int=20] -> (report_md:artifact, digest_line:text) # Render a deterministic Markdown report artifact from a summary table and headline metrics.", "inputs": [{"name": "summary_table", "port_type": "table", "required": true, "description": "Aggregated table with columns and row dicts."}, {"name": "headline_metrics", "port_type": "metrics", "required": true, "description": "Key-value pipeline metrics rendered in the report header."}, {"name": "extra_context", "port_type": "json", "required": false, "description": "Optional structured decision or provenance context."}], "outputs": [{"name": "report_md", "port_type": "artifact", "description": "Deterministic GitHub-Flavored Markdown report string."}, {"name": "digest_line", "port_type": "text", "description": "Single-line summary suitable for logs or notifications."}], "params": [{"name": "title", "param_type": "str", "required": false, "default": "Pipeline Report", "description": "Top-level H1 Markdown heading."}, {"name": "max_rows", "param_type": "int", "required": false, "default": 20, "min_value": 1, "max_value": 200, "description": "Maximum table rows rendered into report_md."}], "function_name": "node_format_markdown_report", "code": {"repository": "https://github.com/ta-amps/seed-packs-library-of-nouns-and-verbs", "folder": {"path": "packs/code-composition/code", "files": 31, "sha256": "0d6c82e4876fd9de57b148d9b6a85b660554978c625631928886060cc1e80179"}, "module": "seed_nodes.py", "code_sha256": "11c195fa0d91473282ab4c974cdcb3071ed65a56ac108fea0787926fb1c4cba6", "source_lines": 31}, "code_license": "MIT", "self_tests": {"cases": 1, "names": ["renders_markdown_artifact"], "with_exact_expected_values": 1, "passed_at_pin": true}, "used_by_recipes": ["ab-candidate-selection", "document-signal-digest", "tabular-anomaly-triage"], "status": "proposal", "admission": "not_admitted", "content_kind": "authored_guidance", "license": "MIT", "provenance": {"source": "original ta-amps authored proposal", "license": "MIT", "generator": "scripts/build_packs.py", "independently_verified": false}, "dimensions": {"determinism": 0.0, "evidence_grounding": 0.0, "token_efficiency": 0.0, "safety_compliance": 0.0, "verification_tier": "unverified"}, "dimension_basis": {"measured": false, "method": "unmeasured_floor", "reason": "Tessera requires these axes, so each is set to its lowest value and the tier is unverified. No quality is claimed. Replace them only with measured values and the evidence that produced them."}, "relations": [{"relation": "requires_noun", "target_id": "seedpack.code-composition/code-composition.v0.2.0.tool.composition-tools", "target_category": "noun.code_node", "note": ""}]}},
{"store": "seedpack.code-composition", "key": "code-composition.v0.2.0.recipe.ab-candidate-selection", "expected_version": 0, "producer_surface": "surface:tessera", "visibility_scope": "surface_only", "allowed_surfaces": [], "target_cohorts": ["all"], "tags": ["category:noun.skill_pack", "pack:code-composition", "role:recipe", "content:authored", "spdx:MIT", "status:quarantined"], "value": {"category_id": "noun.skill_pack", "role": "recipe", "pack": "code-composition", "pack_version": "0.2.0", "title": "Recipe: Holdout A/B Candidate Model Selection with Shrinkage", "category_reason": "A declarative recipe binds catalog nodes into a reusable procedure; Tessera has no separate recipe category.", "recipe": {"edges": [{"dst_port": "rows", "dst_step": "dedupe_rows", "src_port": "rows", "src_step": "ingest_labeled"}, {"dst_port": "rows", "dst_step": "impute_features", "src_port": "rows", "src_step": "dedupe_rows"}, {"dst_port": "rows", "dst_step": "error_ratio", "src_port": "rows", "src_step": "impute_features"}, {"dst_port": "rows", "dst_step": "holdout_partition", "src_port": "rows", "src_step": "error_ratio"}, {"dst_port": "rows", "dst_step": "score_arm_a", "src_port": "holdout_rows", "src_step": "holdout_partition"}, {"dst_port": "rows", "dst_step": "eval_arm_a", "src_port": "rows", "src_step": "score_arm_a"}, {"dst_port": "rows", "dst_step": "score_arm_b", "src_port": "holdout_rows", "src_step": "holdout_partition"}, {"dst_port": "rows", "dst_step": "eval_arm_b", "src_port": "rows", "src_step": "score_arm_b"}, {"dst_port": "candidate_a", "dst_step": "select_winner", "src_port": "eval_metrics", "src_step": "eval_arm_a"}, {"dst_port": "candidate_b", "dst_step": "select_winner", "src_port": "eval_metrics", "src_step": "eval_arm_b"}, {"dst_port": "rows", "dst_step": "cohort_summary", "src_port": "rows", "src_step": "score_arm_b"}, {"dst_port": "summary_table", "dst_step": "decision_report", "src_port": "summary_table", "src_step": "cohort_summary"}, {"dst_port": "headline_metrics", "dst_step": "decision_report", "src_port": "winner_metrics", "src_step": "select_winner"}, {"dst_port": "extra_context", "dst_step": "decision_report", "src_port": "selection", "src_step": "select_winner"}], "external_inputs": [], "goal": "Clean labeled records, hash-split a leak-free holdout partition, evaluate two competing linear risk parameterizations in parallel diamond branches, select the winner via empirical-Bayes shrinkage, and render a decision report.", "recipe_id": "ab-candidate-selection", "steps": [{"description": "Parse labeled historical CSV records.", "node_id": "ingest.csv_rows", "params": {"delimiter": ",", "strip_values": true}, "step_id": "ingest_labeled"}, {"description": "Deduplicate historical cases by case_id.", "node_id": "clean.dedupe_by_key", "params": {"keep": "first", "key_field": "case_id"}, "step_id": "dedupe_rows"}, {"description": "Impute missing numeric features prior to partitioning.", "node_id": "clean.impute_numeric", "params": {"fields": ["errors", "requests", "latency_ms", "label"], "fill_value": 0, "strategy": "median"}, "step_id": "impute_features"}, {"description": "Compute normalized error_rate feature.", "node_id": "feature.ratio_column", "params": {"denominator": "requests", "numerator": "errors", "output_field": "error_rate"}, "step_id": "error_ratio"}, {"description": "Split records deterministically into calibration and holdout sets.", "node_id": "validate.holdout_split", "params": {"holdout_fraction": 0.5, "key_field": "case_id", "salt": "ab-eval-v1"}, "step_id": "holdout_partition"}, {"description": "Score holdout rows with single-feature baseline arm A.", "node_id": "model.linear_risk_score", "params": {"bias": -0.8, "feature_fields": ["error_rate"], "output_field": "risk_score", "weights_csv": "3.0"}, "step_id": "score_arm_a"}, {"description": "Evaluate baseline arm A on the holdout split.", "node_id": "eval.binary_metrics", "params": {"label_field": "label", "score_field": "risk_score", "threshold": 0.5}, "step_id": "eval_arm_a"}, {"description": "Score holdout rows with two-feature challenger arm B.", "node_id": "model.linear_risk_score", "params": {"bias": -2.2, "feature_fields": ["error_rate", "latency_ms"], "output_field": "risk_score", "weights_csv": "9.0,0.008"}, "step_id": "score_arm_b"}, {"description": "Evaluate challenger arm B on the holdout split.", "node_id": "eval.binary_metrics", "params": {"label_field": "label", "score_field": "risk_score", "threshold": 0.5}, "step_id": "eval_arm_b"}, {"description": "Select between arm A and arm B using empirical-Bayes shrinkage.", "node_id": "eval.shrinkage_select", "params": {"count_key": "sample_count", "metric_key": "f1", "min_margin": 0.02, "prior_mean": 0.5, "prior_strength": 4}, "step_id": "select_winner"}, {"description": "Summarize challenger risk distribution across holdout cohorts.", "node_id": "agg.group_summary", "params": {"group_field": "cohort", "value_field": "risk_score"}, "step_id": "cohort_summary"}, {"description": "Render decision artifact with shrunk comparison context.", "node_id": "format.markdown_report", "params": {"max_rows": 15, "title": "A/B Shrinkage Candidate Selection"}, "step_id": "decision_report"}], "title": "Holdout A/B Candidate Model Selection with Shrinkage"}, "recipe_form": "Whole-number floats are written as integers, as Tessera stores them. The compiler reads both forms the same way, but the recipe and plan digests differ from the code folder file's, so both are listed.", "as_stored_here": {"recipe_sha256": "ddd0dc03c95619ab7dbd40da494d6925554ca7cb5384418b9ca1a2342e1f0c74", "plan_sha256": "be45b452d1cdbea8c072589f641635752e9e6f9f7341e2e46efaeb9efcb9704b", "emitted_python_sha256": "75021a5f098f7ef7dcbce3867eafb0657c44c47ca7c56143b2148bb1c9895e07"}, "digest_rules": {"recipe_sha256": "SHA-256 of the recipe's canonical JSON (sorted keys, no spaces), as the compiler records it.", "sample_inputs_sha256": "SHA-256 of the sample inputs' canonical JSON (sorted keys, no spaces).", "file_sha256": "SHA-256 of the recipe file in the code folder with CRLF normalized to LF; the code's own tests check it in CI."}, "compiled_at_pin": {"steps": 12, "edges": 14, "topological_order": ["ingest_labeled", "dedupe_rows", "impute_features", "error_ratio", "holdout_partition", "score_arm_a", "eval_arm_a", "score_arm_b", "eval_arm_b", "select_winner", "cohort_summary", "decision_report"], "entry_inputs": ["ingest_labeled.raw_csv (text)"], "terminal_outputs": ["ingest_labeled.ingest_stats (metrics)", "dedupe_rows.dedupe_stats (metrics)", "impute_features.impute_stats (metrics)", "error_ratio.values (series)", "holdout_partition.train_rows (records)", "holdout_partition.split_stats (metrics)", "score_arm_a.scores (series)", "score_arm_b.scores (series)", "cohort_summary.agg_stats (metrics)", "decision_report.report_md (artifact)", "decision_report.digest_line (text)"], "warnings": 0, "compile_replay_identical": true}, "nodes_used": ["agg.group_summary", "clean.dedupe_by_key", "clean.impute_numeric", "eval.binary_metrics", "eval.shrinkage_select", "feature.ratio_column", "format.markdown_report", "ingest.csv_rows", "model.linear_risk_score", "validate.holdout_split"], "sample_inputs": {"raw_csv": "case_id,cohort,errors,requests,latency_ms,label\nc01,enterprise,18,100,420,1\nc02,enterprise,1,120,45,0\nc03,growth,22,90,510,1\nc04,growth,2,150,55,0\nc05,enterprise,15,80,390,1\nc06,starter,0,200,38,0\nc07,starter,19,85,460,1\nc08,growth,1,140,49,0\nc09,enterprise,25,95,530,1\nc10,starter,2,180,42,0\nc11,enterprise,12,100,480,1\nc12,growth,0,160,41,0\n"}, "sample_inputs_synthetic": true, "sample_inputs_sha256": "b745c14bfdda0a14194ea4af648c74a7fe8516cfb53d175feb9aa09ffdcc0abe", "expected_run": {"conditions": "The recipe as stored here, its sample inputs, a fresh node database with an empty cache and the equivalence check on.", "input_sha256": "621bed2efcf75581d533063941e00237d76da6e05a7a0747b7caedfb8203a649", "output_sha256": "a33da7b5cdb2e7f9fcb292859c11f961feb06ac63b746129499f56e753672d9b", "receipt_sha256": "e13c20258116c8af3ec9b0807e9aee7de58bfa2b98047073cdb078c68a5e476e", "executed_steps": 12, "memo_hits": 0, "python_equivalence_verified": true, "llm_tokens_at_runtime": 0}, "measured": "Compiled and run twice in fresh in-memory databases with the pinned code on October 29, 2026, on Python 3.12.13 and 3.13.13, with identical digests. The recipe, plan, input, output and receipt digests are the same as before the code lost its former name; only the emitted module digest changed, because its header named it. 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