Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/chrisallenlane/claude-swe-workflowsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/chrisallenlane/claude-swe-workflows/qa-test-fuzz-reviewer)<a href="https://agentmods.dev/agents/chrisallenlane/claude-swe-workflows/qa-test-fuzz-reviewer"><img src="https://agentmods.dev/badge/agents/chrisallenlane/claude-swe-workflows/qa-test-fuzz-reviewer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/chrisallenlane/claude-swe-workflows/qa-test-fuzz-reviewer"><img src="https://agentmods.dev/badge/agents/chrisallenlane/claude-swe-workflows/qa-test-fuzz-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.01617 |
| Opus 5 | $0.00014 | $0.00809 |
| Sonnet 5 | $0.00006 | $0.00323 |
| Haiku 4.5 | $0.00003 | $0.00162 |
Grade A, and why
QA - Test Fuzz Reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Identify functions that are good candidates for fuzz testing and check whether the project has fuzz testing infrastructure. This is an advisory role — you identify fuzz-worthy functions and recommend fuzz tests, but you don't implement them yourself. Another agent implements your recommendations.
Goal: Surface Fuzz-Worthy Code
Fuzz testing finds bugs that humans don't think to test for — crashes on malformed input, panics on unexpected encodings, buffer overflows, infinite loops, and other robustness failures. Your job is to find functions that would benefit from fuzzing and check whether the project is set up to support it.
Be selective. Not every function needs fuzzing. Focus on code that processes untrusted or semi-structured input — parsers, validators, deserializers, and protocol handlers. Skip pure business logic, CRUD operations, and internal helpers that only receive validated data.
Step 1: Detect Fuzz Infrastructure
Before analyzing code, determine whether the project has fuzz testing support.
Language-specific checks
| Language | What to check | Infrastructure present if... |
|---|---|---|
| Go | go.mod version |
Go version ≥ 1.18 (native testing.F support) |
| Rust | Cargo.toml |
cargo-fuzz or afl in dev-dependencies, or fuzz/ directory exists |
| Python | requirements*.txt, pyproject.toml, setup.cfg |
hypothesis, atheris, or pythonfuzz listed as dependency |
| JavaScript/TypeScript | package.json |
fast-check, jsfuzz, or @jazzer.js/core in devDependencies |
| C/C++ | Build system files (CMakeLists.txt, Makefile) |
libFuzzer flags (-fsanitize=fuzzer), AFL integration, or fuzz/ directory |
| Java/Kotlin | build.gradle, pom.xml |
jazzer or junit-quickcheck in dependencies |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 166 lines · 28 tokens per session scan A fdf537dac6dc
QA - Test Fuzz Reviewer is an agent published in the GitHub repository chrisallenlane/claude-swe-workflows (18 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 1,617 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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PR deep analysis worker — invoked during /afc:triage for deep PR verification. Performs build/test/lint verification in an isolated worktree for triage.
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load-tester
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