bmad-project-context

Creates and maintains verified AGENTS.md instruction blocks for AI coding agents.

Updated Mar 14, 2026
One-click install
npx skills add https://github.com/ArchaonHW/MingGoRTS --skill bmad-project-context-archaonhw
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bmad-project-context
Source: https://github.com/ArchaonHW/MingGoRTS/tree/main/.agents/skills/bmad-project-context
Command: npx skills add https://github.com/ArchaonHW/MingGoRTS --skill bmad-project-context-archaonhw

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? AI coding agents repeatedly make the same mistakes in a repository because project rules, conventions, and pitfalls are scattered or undocumented. This Skill builds a small, verified, always-loaded instruction block inside AGENTS.md so agents follow the repo's real rules from the first session. ## Core Features & Use Cases - Setup, adopt, refresh, record, and audit modes: Scaffold a new instruction block, migrate existing CLAUDE.md or AGENTS.md content into a managed block, re-verify it against the current codebase, capture observed agent mistakes as pitfalls, and prune stale lines. - Evidence-based verification: Every claim in the block is path-checked and command-verified against the repository, with provenance (date and commit SHA) recorded so later runs can diff against it. - Ledger-driven editing: Existing human-written instructions are never silently deleted; each one is tracked through a retain/rewrite/relocate/automate/delete decision the user approves. - Use Case: A team adopts AI coding assistants on a brownfield repo. Run the adopt intent to convert their existing CLAUDE.md into a verified AGENTS.md block, then use record each time an agent makes a mistake so the pitfall is captured permanently. ## Quick Start Ask the agent to set up the AGENTS.md project context block for this repository using the bmad-project-context skill.

Frequently Asked Questions about bmad-project-context

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an AGENTS.md file for AI coding agents?

Run the skill with the setup intent on a repository that has no meaningful instruction file. It scans the repo, interviews you about rules no scan can find, verifies every claim, and writes a small approved block between managed markers in AGENTS.md.

How do I migrate CLAUDE.md instructions to AGENTS.md?

Use the adopt intent, which treats your existing instruction file as the baseline. Every instruction enters a ledger with a retain, rewrite, relocate, automate, or delete decision you approve, and the old file is typically reduced to an import line once loading is verified.

What belongs in an AGENTS.md instruction block?

Only what changes agent behavior: policy code cannot express, command caveats configs do not state, conventions differing from ecosystem defaults, observed pitfalls, and cross-component rules. Directory trees, stack lists, and style rules enforced by linters are excluded.

Does the skill delete existing instructions automatically?

No. Deletion requires one of four explicit grounds: stale or incorrect, mechanically enforced by a check, harmful or contradictory, or line-item user approval. Every proposed removal is shown in a ledger before anything is written.

How does the refresh mode keep instructions up to date?

Refresh reads the recorded provenance SHA, re-verifies every path and caveat, and runs git log for deletions and renames since that commit. Lines whose evidence is gone become ledger entries for approval, never silent edits.

When should repo rules go in nested AGENTS.md files?

Only when the rules are subtree-exclusive, substantial, materially reduce the root block, and loading is verified for every harness in use. Otherwise rules stay at the root as path-qualified lines, which cost less than a file no agent loads.