GovernSpec AGENTS.md

AGENTS.md

Project goal

GovernSpec is a local-first CLI and schema for describing AI tasks as explicit contracts.

Setup

• Install dependencies: pip install -e ".[dev]"
• Run tests: pytest
• Run CLI locally: governspec --help

Architecture

• governspec_core.spec — YAML parser, Pydantic models, and schema generation
• governspec_core.iir — Intermediate Intent Representation builder
• governspec_core.targets — compile-to-target logic (agents-md, openai-structured, etc.)
• governspec_core.importers — reverse import from existing artifacts (AGENTS.md, Cursor Rules, OpenAI/Gemini JSON)
• governspec_core.draft — enhanced heuristic draft generator (CJK + English)
• governspec_core.testing — offline acceptance test runner
• governspec_cli — Typer CLI (governspec command)
• governspec_mcp — thin MCP server

Code style

• Use Python 3.11+ with type annotations.
• Keep the MVP local, deterministic, and easy to test.
• Prefer small, surgical changes over speculative abstractions.
• Use Pydantic v2 models and Typer CLI patterns consistently.
• Centralize shared logic (e.g. _parsing.py for importers, build_draft_payload for payload construction).
• Pattern tuples in heuristic modules should only carry elements that are actually used.

Safety boundaries

• Do not call real LLM APIs.
• Do not require network access in tests.
• Do not introduce real outbound network workflows.
• Do not make examples depend on real API keys.
• Do not add automatic high-risk actions.

Maintenance rules

• Add or update tests for every behavior change.
• When changing model fields, update examples, JSON schema, README, and tests together.
• Keep CLI behavior aligned with the documented acceptance criteria.