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docs: add guidance for contributors using AI coding agents
Maintainers are seeing more AI-assisted pull requests. The rules for them already exist across this guide (branch off v8, one concern per PR, regression tests that fail before the fix, never hand-edit generated skills, Co-Authored-By disclosure), but an agent or a new contributor has to piece them together. This adds a short "Working with AI Coding Agents" section under Pull Requests that collects those existing rules in one place. It adds no new policy. It also mentions ContribOS as an optional tool that reads these rules and checks a branch against them; the maintainer agreed to a PR for it on X. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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@@ -124,6 +124,17 @@ Use a conventional-commit prefix (e.g., `fix:`, `feat:`, `docs:`, `fix(extract):
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- Keep description synchronized with final implementation.
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- Rebase/resolve conflicts before requesting final review.
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## Working with AI Coding Agents
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AI assistants are welcome, but every rule in this guide applies to the code they write, and you remain the author of the PR.
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- Point your agent at this file and [ARCHITECTURE.md](ARCHITECTURE.md) before it changes anything.
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- Branch off `upstream/v8`, keep the PR to one concern, and never let an agent hand-edit generated skill files.
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- For bug fixes, confirm the regression test fails without the fix, not only that it passes with it.
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- Run the checks yourself before opening the PR: `uv run pytest tests`, `uv run ruff check .`, `uv run pyright`.
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- Disclose material AI help with a `Co-Authored-By:` trailer, as described under [Commit Messages](#commit-messages).
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- Write the PR description yourself, and list the commands you actually ran.
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Optional: [ContribOS](https://github.com/adityatiwari101104/contribos) can list these rules with file and line references (`contribos policy Graphify-Labs/graphify`) and review a branch against them before you open a PR (`contribos check`).
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## Issue Reports
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### Bugs
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Include exact version/commit, environment, minimal reproduction, expected vs actual, logs, graph/cache artifacts where relevant, and whether a clean checkout reproduced it.
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