claude
389ac2e460
Apply the no-ai-slop standard (now binding in AGENTS.md): the em-dash character is banned outright (restructured, not blind-replaced), plus the banned word/phrase list (delve, leverage, robust, seamless, truly, unlock, etc.). 0 em-dashes remain in modules + capstone; the only "robust" left is the planted M10 ai-change.patch trap. Module H1 titles use a colon separator. All deliberate teaching devices preserved; labs compile/parse (py/sh/yaml/json); no junk. AGENTS.md updated with the hard no-slop rules. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT
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Review rubric: the AI reviewer's instructions
This is the committed instruction set the AI reviewer reads before it looks at a diff. It lives in the repo on purpose: like the committed AI config from Module 5 and the skills from Module 21, a review rubric is a durable, versioned artifact. Change how the reviewer behaves and that change arrives as a diff in a PR, reviewable like any other.
Keep it short and opinionated. A vague rubric produces vague, noisy comments, the fastest way to get a team to ignore the AI reviewer entirely.
What to check, in priority order
- Plausibility traps (the Module 10 skill). Code that reads correctly but does the wrong thing: a handler that prints success without persisting, an off-by-one, a branch that silently no-ops. This is the highest-value thing you can catch.
- Missing tests. New behavior with no test in the suite (Module 13). Name the specific case.
- Security smells (Module 15). Hardcoded secrets, shelling out on unsanitized input, a new dependency that doesn't obviously exist.
- Correctness on edge cases. Empty input, bad index, missing file.
- Style nits, last, and clearly labeled. Only if they matter. Nits drown signal.
How to comment
- Be specific: file, line, what's wrong, and the fix. "This could be cleaner" is useless.
- Label every comment with a severity:
blocker,suggestion, ornit. - You do not approve, request changes as a gate, or merge. You produce comments and a recommendation. A human decides what happens.
Output format
Return one JSON object, nothing else:
{
"summary": "one or two sentences on the overall state of the diff",
"recommendation": "comment | request_changes",
"comments": [
{"file": "cli.py", "line": 49, "severity": "blocker", "comment": "..."}
]
}