bmad-project-context

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

Updated Sep 3, 2026
One-click install
npx skills add https://github.com/watchthelight/shatterfish --skill bmad-project-context-watchthelight
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bmad-project-context
Source: https://github.com/watchthelight/shatterfish/tree/main/.claude/skills/bmad-project-context
Command: npx skills add https://github.com/watchthelight/shatterfish --skill bmad-project-context-watchthelight

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-specific rules, pitfalls, and conventions are never written down where agents load them. This Skill interviews the user, scans the repository, and produces a small verified instruction block inside AGENTS.md so agents follow the team's actual rules. ## Core Features & Use Cases - Setup and Refresh: Scans repo config, CI, and source to build or update a verified AGENTS.md block, with provenance lines recording the date and commit SHA for later diffing. - Record and Audit: Captures observed agent mistakes as pitfall lines the moment they happen, and re-verifies every line on audit, pruning only what no longer changes behavior. - Use Case: After an agent repeatedly runs plain pytest instead of uv run pytest in your project, invoke the record intent to add the exact working invocation to the block so no agent makes that mistake again. ## Quick Start Ask the agent to run the bmad-project-context skill to set up the AGENTS.md instructions for this repository.

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's setup intent against your repository. It scans config files, CI, and source, interviews you only about what scans cannot answer, then shows the complete block for approval before splicing it between markers in AGENTS.md.

What should go in agent instructions for a repository?

Only what an agent cannot derive by reading the repo: policy the code cannot express, caveats about running the project, conventions differing from ecosystem defaults, and pitfalls with observed evidence. Repo overviews, style rules, and commands already in package.json or CI config are excluded.

How do I record a mistake an AI agent made in my repo?

Use the record intent with the task, the mistake, the correction, and its evidence. One occurrence is noted; a recurring or costly mistake earns a pitfall line or an exact command line, and mechanically preventable issues are routed to a hook, lint rule, or CI check instead.

Does the skill write to my repository without approval?

No. The skill is conversational and never writes until it shows the complete block and receives your approval. It splices content only between markers, leaves everything outside byte-identical, and never commits.

How does refresh keep AGENTS.md from going stale?

Refresh reads the provenance line's recorded SHA, re-verifies every path and caveat, and runs git log for deletions and renames since that SHA against every line. Lines whose evidence is gone are updated or removed, and the interview shrinks to what changed.

When should a subdirectory get its own AGENTS.md?

A component or nested repository gets its own file when work keeps landing there and its rules do not belong at the parent level. Rules bounded to a directory go in a nested AGENTS.md attached by location, and every child is listed in the parent's Where things are section.