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spec-new

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Actualizado1 de julio de 2026 a las 01:30

Scaffold a new spec-driven feature in AlphaGalerkin — creates a specs/<feature>.spec.md from specs/TEMPLATE.spec.md and the mirrored src/ module + tests/ stubs. Use when starting any new PoC scenario, PDE operator, agent type, or module so the spec (data contract + acceptance criteria + MetricThreshold thresholds) is written before the code.

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Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.

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ianshank

ianshank/AlphaGalerkin

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SKILL.md

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name	spec-new
description	Scaffold a new spec-driven feature in AlphaGalerkin — creates a specs/<feature>.spec.md from specs/TEMPLATE.spec.md and the mirrored src/ module + tests/ stubs. Use when starting any new PoC scenario, PDE operator, agent type, or module so the spec (data contract + acceptance criteria + MetricThreshold thresholds) is written before the code.

spec-new — scaffold a spec-driven feature

AlphaGalerkin uses spec-driven development: write the contract before the code. This skill bootstraps that flow for a new feature named $FEATURE.

Steps

Copy the template: create specs/$FEATURE.spec.md from specs/TEMPLATE.spec.md. Fill in Context (link the CLAUDE.md Next-Steps row / ROI tier), User Story, Data Contract, Acceptance Criteria, and the Thresholds table.
Thresholds = existing type: express every pass/fail criterion as a src.poc.config.MetricThreshold(name, operator, value). Do not invent a new threshold schema — the feature's Pydantic config get_default_thresholds() is the single source of truth.
Mirror the layout: create the module under src/<pkg>/ and its test under tests/<pkg>/ (identical relative path). Follow the closest existing precedent (src/poc/scenarios/scaling_law.py + scaling_law_config.py for scenarios; src/pde/operators.py for PDE operators; src/agents/*.py for agents).
Config first: every tunable is a typed Field(default=…, <bounds>, description=…). Surface numerical-stability literals as named module constants.
AQA test: add a test asserting the config's get_default_thresholds() returns exactly the metrics/operators the spec's Thresholds table documents (spec ↔ config agreement).
Register the regression surface: add the feature's test command block to the Regression Surface table in CLAUDE.md.

Guardrails

Additive/backwards-compatible only: new files, new optional fields, new registry keys.
ruff + mypy --strict clean on the changed surface; tests to the 85% coverage gate.
Read specs/README.md for the full workflow.

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name	spec-new
description	Scaffold a new spec-driven feature in AlphaGalerkin — creates a specs/<feature>.spec.md from specs/TEMPLATE.spec.md and the mirrored src/ module + tests/ stubs. Use when starting any new PoC scenario, PDE operator, agent type, or module so the spec (data contract + acceptance criteria + MetricThreshold thresholds) is written before the code.

spec-new — scaffold a spec-driven feature

AlphaGalerkin uses spec-driven development: write the contract before the code. This skill bootstraps that flow for a new feature named $FEATURE.

Steps

Copy the template: create specs/$FEATURE.spec.md from specs/TEMPLATE.spec.md. Fill in Context (link the CLAUDE.md Next-Steps row / ROI tier), User Story, Data Contract, Acceptance Criteria, and the Thresholds table.
Thresholds = existing type: express every pass/fail criterion as a src.poc.config.MetricThreshold(name, operator, value). Do not invent a new threshold schema — the feature's Pydantic config get_default_thresholds() is the single source of truth.
Mirror the layout: create the module under src/<pkg>/ and its test under tests/<pkg>/ (identical relative path). Follow the closest existing precedent (src/poc/scenarios/scaling_law.py + scaling_law_config.py for scenarios; src/pde/operators.py for PDE operators; src/agents/*.py for agents).
Config first: every tunable is a typed Field(default=…, <bounds>, description=…). Surface numerical-stability literals as named module constants.
AQA test: add a test asserting the config's get_default_thresholds() returns exactly the metrics/operators the spec's Thresholds table documents (spec ↔ config agreement).
Register the regression surface: add the feature's test command block to the Regression Surface table in CLAUDE.md.

Guardrails

Additive/backwards-compatible only: new files, new optional fields, new registry keys.
ruff + mypy --strict clean on the changed surface; tests to the 85% coverage gate.
Read specs/README.md for the full workflow.