bmad-document-project

bmad-document-project is a skill for Claude Code, Codex from jeffrey2423/commit-like-pro. It costs 29 tokens per session (591 once invoked), scanned A, a copy of bmad-document-project, MIT.

A workflow for documenting an existing software project so AI agents can understand it. A brownfield project is an existing codebase rather than a newly started one.

In plain words
What is it for?
Use it to generate project documentation for AI-assisted development, including the project's configured workflow and any applicable team or personal overrides.
Why use it?
It captures the project's structure and important context, reducing the chance that an agent misunderstands how the codebase works.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jeffrey2423/commit-like-pro/bmad-document-project
Any agent
npx skills add jeffrey2423/commit-like-pro --skill bmad-document-project
Clone the repo
git clone --depth 1 https://github.com/jeffrey2423/commit-like-pro

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for bmad-document-project

README.md
[![agentmods](https://agentmods.dev/badge/skills/jeffrey2423/commit-like-pro/bmad-document-project.svg)](https://agentmods.dev/skills/jeffrey2423/commit-like-pro/bmad-document-project)
Your own site
<a href="https://agentmods.dev/skills/jeffrey2423/commit-like-pro/bmad-document-project"><img src="https://agentmods.dev/badge/skills/jeffrey2423/commit-like-pro/bmad-document-project.svg" alt="Measured on agentmods" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 591 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00029 $0.00591
Opus 5 $0.00015 $0.00296
Sonnet 5 $0.00006 $0.00118
Haiku 4.5 $0.00003 $0.00059

Measured 3d ago against content hash 806d73f66a8f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

bmad-document-project scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to bmad-document-project — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/skills/bmad-document-project/SKILL.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Document Project Workflow

Goal: Document brownfield projects for AI context.

Your Role: Project documentation specialist.

Conventions

  • Bare paths (e.g. instructions.md) resolve from the skill root.
  • {skill-root} resolves to this skill's installed directory (where customize.toml lives).
  • {project-root}-prefixed paths resolve from the project working directory.
  • {skill-name} resolves to the skill directory's basename.

On Activation

Step 1: Resolve the Workflow Block

Run: python3 {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --key workflow

If the script fails, resolve the workflow block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:

  1. {skill-root}/customize.toml — defaults
  2. {project-root}/_bmad/custom/{skill-name}.toml — team overrides
  3. {project-root}/_bmad/custom/{skill-name}.user.toml — personal overrides

Any missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by code or id replace matching entries and append new entries, and all other arrays append.

Step 2: Execute Prepend Steps

Execute each entry in {workflow.activation_steps_prepend} in order before proceeding.

Step 3: Load Persistent Facts

Treat every entry in {workflow.persistent_facts} as foundational context you carry for the rest of the workflow run. Entries prefixed file: are paths or globs under {project-root} — load the referenced contents as facts. All other entries are facts verbatim.

Step 4: Load Config

Load config from {project-root}/_bmad/bmm/config.yaml and resolve:

  • Use {user_name} for greeting
  • Use {communication_language} for all communications
  • Use {document_output_language} for output documents
  • Use {planning_artifacts} for output location and artifact scanning
  • Use {project_knowledge} for additional context scanning

Step 5: Greet the User

Greet {user_name} (if you have not already), speaking in {communication_language}.

Read the full file on GitHub · 63 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 63 lines · 29 tokens per session scan A 806d73f66a8f

Subscribe to this mod's changes

bmad-document-project is a skill published in the GitHub repository jeffrey2423/commit-like-pro (2 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 591 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to bmad-document-project, differing in 0 lines, and is treated as a copy.

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