npx agentspec-cli install 33be2fec-f3ea-440c-8355-31850c22a8fb --file-type gemini-md→ GEMINI.md
<!-- GENERATED: source=AGENTS.md format-version=1 sha256=f872fbd69c0feb2732866dfad848d652fb6789fab35100df61adf7d76b0746bc --> > Generated from `AGENTS.md`. Edit `AGENTS.md`, then rerun `scripts/sync-ai-docs.sh --write`. > If this file conflicts with `AGENTS.md`, `AGENTS.md` wins. > Gemini-specific refresh behavior belongs in tooling, not in a second policy file. # AGENTS.md > Canonical AI policy for this repo. > If model-specific mirrors exist, generate them from this file. ## Project Pituitary is a consistency governance tool that keeps specifications, documentation, and code aligned. It builds a temporal, confidence-weighted governance graph from spec bundles and docs, then runs overlap, drift, compliance, impact, and freshness analysis against it. The current repo is focused on local filesystem inputs, Markdown docs, SQLite-backed indexing, a CLI-first interface, an optional MCP wrapper, and repo CI validation. ## Coding Standards - Read [README.md](README.md) and [ARCHITECTURE.md](ARCHITECTURE.md) before deep implementation work. Use the active GitHub issues for backlog and priority context. - If you touch core write paths or repo governance, also read [docs/development/repo-governance.md](docs/development/repo-governance.md). - Treat repository docs as the primary source of truth; keep GitHub issues aligned with them rather than the reverse. - Prefer small, reversible changes and deterministic tooling over hand-maintained generated state. - Keep outputs machine-readable where the architecture expects JSON-first behavior. ## Architecture Rules - First ship is CLI-first. Keep the CLI as the required transport and do not make core behavior depend on MCP, even though the repo also ships an optional MCP wrapper. - Scope is local filesystem only: `spec.toml` + `body.md` bundles, Markdown docs, SQLite, and `sqlite-vec`. - The repo ships CI for fmt, readiness, test, and vet validation, but GitHub- or vendor-specific reporting integrations remain out of scope. - Spec and doc analysis come before code-compliance features. - Canonical contract decisions live in `ARCHITECTURE.md`; update repo docs and GitHub issues together when those contracts change. ## Workflow - Keep GitHub issues aligned with the repo docs and in priority order. - When planning or implementing, name the files you expect to touch and why. - Run `git status` and `git diff --minimal` before any commit. - Stage explicit paths. Never use `git add .`. - Show diffs and wait for approval before committing or pushing. ## Testing - Run the smallest check that proves the change. - Prefer `make fmt`, `make test`, `make vet`, and `make ci` where applicable. - If you skip validation, state the reason explicitly. ## Safety - No secrets in tracked files, docs, or fixtures. - Stay within the active issue or approved work item and call out scope drift when it appears. - Do not overwrite user changes or reset the worktree without explicit approval.
AGENTS.md - Universal AI Agent Configuration
This file provides comprehensive guidance for AI agents working with code in this repository.
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AGENTS.md — agents-md-generator
`agents-md-generator` is a Python-based MCP (Model Context Protocol) server designed to generate and maintain `AGENTS.md` files—architectural context documents for AI coding agents. It uses Tree-sitter for high-fidelity AST analysis across multiple languages (Python, TypeScript, Go, C#) and `uv` for dependency management. The system operates as an incremental, cache-aware pipeline that transforms a codebase into a structured payload for AI assistants to perform maintenance tasks without manual e
by AgentHub Crawler
AGENTS.md
This file provides guidance to AI coding agents (Claude Code, Gemini, etc.) when working with code in this repository. `CLAUDE.md` and `GEMINI.md` are symlinks to this file.
by AgentHub Crawler
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CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
by AgentHub Crawler