bmad-project-context

Creates and maintains verified AGENTS.md instruction blocks for AI agents in a repository.

6|Updated Aug 29, 2026
One-click install
npx skills add https://github.com/HordRicJr/Akomagni --skill bmad-project-context-hordricjr
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bmad-project-context
Source: https://github.com/HordRicJr/Akomagni/tree/main/bmad-core/.agents/skills/bmad-project-context
Command: npx skills add https://github.com/HordRicJr/Akomagni --skill bmad-project-context-hordricjr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Repositories accumulate stale, bloated, or missing agent instructions, causing AI coding agents to repeat mistakes, violate team policies, and run wrong commands. This Skill produces a small, verified AGENTS.md block containing only what agents cannot derive from the repo itself. ## Core Features & Use Cases - Setup and Refresh: Scans the repository, interviews the user for governance and conventions, and writes a verified instruction block between markers in AGENTS.md, with provenance tracking via commit SHA. - 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: A team lead notices agents keep running plain pytest instead of uv run pytest and pushing to main. They invoke the skill, which verifies the correct invocation from project config, interviews for branch policy, and writes a concise AGENTS.md block the whole team shares. ## Quick Start Ask the AI to set up the AGENTS.md agent instructions 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 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 for policies and conventions no scan can find, then writes a small approved block 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 branch rules and frozen paths, caveats about running tests, conventions differing from ecosystem defaults, and observed pitfalls. Exclude directory trees, stack lists, and commands already stated in package.json or CI config.

How do I record mistakes AI agents make in my repo?

Use the record intent when an agent makes a mistake. The skill captures the task, mistake, correction, and evidence, then adds a pitfall line or exact command correction to the block, proposing a hook or CI check if the error is mechanically preventable.

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

No. Writes are spliced only between the block markers, leaving everything outside byte-identical, and the user approves the complete block before any write. It never commits changes to the repository.

When should agent instructions be refreshed or audited?

Refresh after significant repository changes; the skill diffs deletions and renames since the recorded commit SHA and re-verifies every line. Audit re-checks caveats and removes lines whose removal would not change agent behavior.