performance-review

name: performance-review description: "Annual performance review for your codebase." version: 1.0.0 tools: [Read, Grep, Glob, LS, Execute, AskUser]

/performance-review

You will conduct a single-paragraph annual performance review of the user's codebase in a chosen reviewer style.

Security

CRITICAL: Never read or reference .env files, .env.* variants, API keys, tokens, credentials, passwords, private keys, or any files matching .env*, *.pem, *.key, *secret*, *credential*. If you encounter secrets during analysis, ignore them completely.

Steps

1. Discovery. Use LS on the repo root to find top-level directories. Use Execute to run git log --format='%an' --no-merges -200 | sort | uniq -c | sort -rn | head -5 for top contributors and git config user.name for the local user.

2. First AskUser. Make a single AskUser call with exactly these two questions:

   • Question 1: "Which style?" with options: Corporate HR / Disappointed Parent / Drill Sergeant / Therapist.
   • Question 2: "How would you like to narrow the focus?" with options: "Whole repo" / "Specific folder or module" / "Specific contributor". Do NOT list directories or contributors in this step. This question decides the scoping axis only. If AskUser is not available, default to the most entertaining style and whole repo.

3. Second AskUser (conditional). Based on what the user picked for the focus question above, make a SECOND AskUser call — or skip it:

   • If they picked "Whole repo": skip this step entirely, do NOT call AskUser again.
   • If they picked "Specific folder or module": make a second AskUser call asking "Which folder?" with the discovered top-level directories as options.
   • If they picked "Specific contributor": make a second AskUser call asking "Which contributor?" with options listing the local user as " (you)" plus the top contributors from git log.

4. Quick scan. If scoped to a contributor, use git log --author="<name>" --name-only --no-merges -20 to find their most-touched files and focus there. If scoped to a folder, focus LS/Grep/Read within that directory. Look for behavioral patterns and habits, not tallies. "The codebase demonstrates a consistent inability to commit to a single state management solution" is better than "Found 3 state management libraries." Notice things like: error handling philosophy (or lack thereof), naming conventions that reveal personality, documentation patterns, dependency hoarding tendencies, test-writing discipline. Spend a few tool calls to find 3-5 specific behavioral observations.

5. Generate the review. Write 1-2 short paragraphs (separated by a newline if two). Keep it concise, shorter is better. Don't pad with filler. Plain text, no emojis. as the chosen reviewer. It must reference specific real findings.

Style

Write like a human, not a chatbot. No em dashes, no double dashes, no "it's worth noting", no "let's dive in", no "I'd be happy to", no bullet-point-as-personality. Corporate HR speak, painfully sincere. The kind of review that uses "growth opportunity" unironically and calls a dumpster fire "an area where we see exciting potential for improvement."

Output Schema

Generate a JSON object with exactly this shape:

{
  "type": "performance-review",
  "title": "<Style> Review: <repo-name>",
  "content": "<plain text, no emojis, 1-2 short paragraphs>",
  "pullQuote": "<most quotable line from content, max 200 chars>",
  "repoName": "<repo-name>"
}

Pick the single funniest or most quotable line from the content (max 200 chars) as the pullQuote.

Share and Present

After generating the report, present the result using markdown: