Reply to review comments

Model notes: Any model

Fill in the variables (optional — they're inserted live below):

I got these review comments on my pull request. Help me respond well. My change: {{diff_or_code}} Review comments: {{review_comments}} For each comment: 1. Is the reviewer right, partly right, or mistaken? Explain in one or two sentences, based on the code. 2. Suggested action: change the code (show the change), push back politely (with a reason), or ask a clarifying question. 3. A short, friendly reply I can post. No defensiveness, no grovelling. If two comments conflict, point that out. If a comment reveals a real bug I missed, put it at the top.

How to use it

  1. Fill the variables above, or replace each {{variable}} after pasting.
  2. Paste into your AI tool (ChatGPT, Claude, Gemini, Cursor, Claude Code, or a local model in Ollama/LM Studio).
  3. Review the output. Models make mistakes, especially with facts, numbers and code.
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More Code review prompts

Code review

Senior code review of a diff

Claude/GPT-class models; paste a git diff

Variables: diffwhat_the_change_does

Review this diff as a senior engineer who cares about correctness first, then clarity.

```diff
{{diff}}
```
Context: {{what_the_change_does}}

Output:
1. **Blocking issues** (bugs, security, data loss, race conditions) with line references and a suggested fix.
2. **Should fix** (error handling, edge cases, missing tests).
3. **Nits** (naming, style): max 5.
4. What's good about the change (1-2 lines).
If you're unsure whether something is a bug, say so and explain what would confirm it. Don't invent issues to fill sections.
Open & fill variables: Senior code review of a diff →
Code review

Security review

Not a substitute for a real audit

Variables: app_typecode

Do a focused security review of this code for a {{app_type}} app:

```
{{code}}
```

Check specifically for: injection (SQL, command, template), XSS, auth/authorisation gaps (IDOR), secrets in code, unsafe deserialisation, SSRF, path traversal, missing rate limits, insecure defaults, and dependency risks you can see.
For each finding: severity (high/med/low), exploit scenario in one sentence, and the fix. If nothing is found in a category, say "none found" rather than speculating.
Open & fill variables: Security review →
Code review

Review AI-generated code

Use on agent output before merging

Variables: code

This code was written by an AI assistant. Review it with that in mind:

```
{{code}}
```

Look for typical AI-code problems: invented APIs or library functions that don't exist, outdated syntax, silently swallowed errors, over-engineering, duplicated helpers that already exist in the codebase, tests that don't really test anything, hard-coded values, and comments that don't match the code.
List each problem with the fix. Then rate: merge / merge after fixes / rewrite.
Open & fill variables: Review AI-generated code →

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