Generates a Conventional Commits message from a diff or a plain description, picking the right type and scope, using imperative mood, and flagging breaking changes correctly.
Version 1 · 2 variables · 1 required
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Showing all 1 public result from Claude Sonnet 5 on version 1.
Contributor notes: Illustrative example — not an actual model run. Written to show the shape of a good answer so the prompt can be judged before you spend a call on it. Attribution: adapted from https://github.com/f/awesome-chatgpt-prompts by jeff-nasseri, licensed CC0-1.0. Source file: https://github.com/f/awesome-chatgpt-prompts/blob/main/PROMPTS.md
1 public result from 1 model
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Turns a project idea into a complete scaffold: a summary, build steps, directory structure, the purpose of each file, commented source for every file, a setup script and a README.
**Summary** Rate limiting for the public search endpoint moves from a per-process in-memory counter to a shared Redis counter, so the limit now applies across all application instances rather than per instance. **Files Changed** - `src/middleware/rate_limit.py` — replaces the module-level `defaultdict` with a Redis-backed sliding window. - `src/config.py` — adds `REDIS_URL` and `SEARCH_RATE_LIMIT_PER_MINUTE`, both required at startup. - `tests/test_rate_limit.py` — new tests covering the wind
Turns raw git diff output into a structured PR description covering summary, files changed, significant code, reasoning, project impact, a test plan and reviewer notes.
### Overall Assessment The function's intent is immediately obvious, which is a real strength — nobody will misread what it returns. Its two weaknesses are both structural rather than cosmetic: it issues one database round trip per user, and it raises an unhandled exception the first time an id has no matching row. ### Prioritized Recommendations 1. Replace the per-id query with a single `IN` query to eliminate the N+1 pattern. 2. Decide explicitly what should happen when a user id has no row
Reviews a snippet or diff across correctness, security, performance, readability, idiom and error handling, then returns prioritized fixes with before/after code and a rationale for each.
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