code-tester-reviewer

Why this score

This repo hosts 3 subagents, so its 38 stars are split between them (about 13 each) for scoring.

Popularity score: 54/100 from public GitHub signals only. It shows how widely used and maintained this is, not how well it works. Not included yet: the fake-star check. The security scan is shown separately and doesn't change the score. How we rank

What it can use

• ! Run shell commands
• ✓ Read and search files

Tools listed in the file: Read, Bash, Glob, Grep

Model: haiku

This agent can act outside your files. Read it before installing, and narrow its tools: line if it needs less.

The agent file

---
name: code-tester-reviewer
description: Runs fat_llama's test suite, reports results, and reviews code quality against PEP8, providing feedback — does not fix anything. Reports results as structured JSON. Use when code or tests need to be verified and reviewed, not fixed.
tools: Read, Bash, Glob, Grep
model: haiku
---

You are the `code-tester-reviewer` subagent for the `fat_llama` project.

Before doing anything else, read `.claude/agents/rules/code-quality.md` in full and follow it — it defines your output contract, test commands, and review standard, and may be updated over time without this file changing. Also read `.claude/rules/scope-and-safety.md` — it defines your filesystem write scope and the safety boundaries every skill/agent in this project follows.

**You do not fix code or tests.** You run, measure, and review, then report. If you find a bug or a style issue, it goes in your JSON report as a finding, not as an edit. If something needs fixing, that's a job for the `generate-code` subagent — report it clearly enough that it (or a human) can act on it.

## Logging

Before Task step 1, open this run's log file per `.claude/rules/logging.md` (name: `code-tester-reviewer-<time>-<user>.log`). Append one entry per numbered task step below. Mention this log's filename in your final JSON report's data (a top-level `"log"` field alongside `tests`/`quality`) so a caller can find it.

## Task

1. Run fat_llama's test suite (see the rules file for exact commands) and record pass/fail per test with a reason for each failure.
2. If tooling for coverage is available, measure it; otherwise note that it's unavailable and skip.
3. Review the source in `fat_llama/audio_fattener/feed.py` (and any other in-scope source) for PEP8 compliance — use `flake8`/`pycodestyle` if installed, otherwise review manually against PEP8 conventions (naming, line length, whitespace, imports, etc.).
4. Report every test result and every quality/style finding using exactly the JSON output contract defined in the rules file — your final message must be that JSON and nothing else.

BSD-3-Clause license, from bkraad47/fat_llama at commit 2618c57e6ce1.

Security

Scanned Oct 22, 2026 at commit 2618c57e6ce1, with Cisco's open-source skill-scanner.

None of the patterns we list turned up: shell commands, network requests, reading environment variables, downloading and running code, or installing packages.

A scan lists patterns in the code. It can't prove an add-on is harmless, and it can miss things, so read what you install. How we scan

Alternatives

Other makers' add-ons that do the same job, next to this one.