agentleFS
a-novel-kita-novel-kit/stack/.agents/skills/attribute-ai-commits/SKILL.md

attribute-ai-commits

Skill2 starsChanged 4 days agoMITView on GitHub

Attribute AI contributions when writing, amending, or reviewing commit messages. Use the verified repository registry; delegate missing identities to register-ai-agent.

The file

We split this skill into the rules it gives an agent

7 rules. About 0 are common, 4 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈4

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Keep the human as Git author and committer.

    line 10
  2. Distinctive:

    Look up the agent without network access:

    line 20
  3. Distinctive:

    When a verified agent materially contributed to the commit, append:

    line 40
  4. Very specific:

    Use the exact token Co-authored-by: and keep one blank line before the trailer block.

    line 48
  5. Very specific:

    Start with the registry label.

    line 53
  6. Distinctive:

    Do not guess or derive a hidden model name.

    line 55
  7. Distinctive:

    Do not add the trailer when the agent only inspected or reviewed the work, formatted a user-written commit message, or performed no …

    line 68

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Attribute AI Commits

Keep the human as Git author and committer. Add the contributing AI agent as a standard Co-authored-by: trailer only when the repository registry maps its email to a real, provider-controlled GitHub account.

Resolve the current agent

Determine the agent product that performed the work. Do not substitute the model provider for a third-party agent client: a Mistral model running inside another coding agent belongs to that client.

Look up the agent without network access:

node <skill-dir>/scripts/coauthor-registry.mjs lookup <agent>

Interpret the result:

  • Exit 0, status: verified: use the registered identity. Do not revalidate it.
  • Exit 2, status: unavailable: omit the co-author trailer. Do not search again.
  • Exit 3, status: missing: load and follow the register-ai-agent skill.
  • Exit 1: treat it as an operational error and omit the trailer.

The pushed registry is the durable memory. Do not create a private cache, Git config entry, expiry, or periodic verification job for registered agents. The initial registry is an exhaustive baseline of mainstream repository-capable coding and code-review agents as of its as_of date; inspect it with coauthor-registry.mjs list.

Write the trailer

When a verified agent materially contributed to the commit, append:

<commit subject and optional body>

Co-authored-by: <display name> <verified email>

Use the exact token Co-authored-by: and keep one blank line before the trailer block. Put each co-author on its own line with no blank lines between co-authors.

Build the display name as follows:

  • Start with the registry label.
  • Append the exact model display name when the runtime exposes it reliably.
  • Do not guess or derive a hidden model name.

Examples:

Co-authored-by: Codex GPT-5.6 Sol <noreply@openai.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: gemini-cli Gemini 3.5 Pro <218195315+gemini-cli@users.noreply.github.com>

GitHub links by the verified email, so adding the model to the display name preserves the provider account mapping while making model usage visible.

Do not add the trailer when the agent only inspected or reviewed the work, formatted a user-written commit message, or performed no material work included in the commit.

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Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.