bmad-project-context

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

1|Updated Jun 2, 2026
One-click install
npx skills add https://github.com/SevWren/Daily-Motivation-Brain-Helper --skill bmad-project-context-sevwren
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bmad-project-context
Source: https://github.com/SevWren/Daily-Motivation-Brain-Helper/tree/main/.claude/skills/bmad-project-context
Command: npx skills add https://github.com/SevWren/Daily-Motivation-Brain-Helper --skill bmad-project-context-sevwren

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Repositories accumulate stale, bloated, or missing agent instruction files, causing AI coding agents to repeat mistakes, violate team policies, and waste context on derivable facts. This Skill produces a small, verified AGENTS.md block containing only what the repository itself cannot tell an agent. ## Core Features & Use Cases - Setup and Refresh: Scans the repo, interviews the user only for what scans cannot answer, and writes a verified instruction block between markers with provenance (date and commit SHA) for future diffs. - Record and Audit: Captures observed agent mistakes as pitfall lines the moment they happen, and re-verifies every line on audit, pruning what no longer changes agent 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 AGENTS.md so no agent makes that mistake again. ## Quick Start Ask the agent to set up the AGENTS.md agent instructions block for this repository using bmad-project-context.

Frequently Asked Questions about bmad-project-context

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

FAQPage Schema
How do I set up AGENTS.md instructions for AI coding agents?

Invoke the skill with the setup intent against your repository. It scans configs, CI, and source for verifiable facts, interviews you only for what scans cannot answer, then shows the complete block for approval before writing it between markers in AGENTS.md.

What should go in an AGENTS.md file for AI agents?

Include only what agents cannot derive from the repo: policy like frozen paths and branch rules, caveats about running tests, conventions differing from ecosystem defaults, and pitfalls with observed evidence. Exclude directory trees, stack lists, and commands already stated in package.json or CI config.

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 invocation in the block, and mechanically preventable issues are proposed as hooks or CI checks instead.

Does the skill modify files outside the AGENTS.md block?

No. It splices content only between the bmad:context markers, leaving everything outside byte-identical, and never commits. When other instruction files contradict the block, it proposes fixes but requires your approval for every write.

How does refresh keep agent instructions from going stale?

Refresh reads the provenance line's commit 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 rules go in a nested AGENTS.md instead of the root?

Rules bounded to a specific directory go in a nested AGENTS.md at that location, attached by path rather than by pointer. A component or child repo gets its own file only when work keeps landing there and its truths do not belong at the parent level.