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.
npx skills add codebygarv/Ai-skills --skill fuzz-testing-designergit clone --depth 1 https://github.com/codebygarv/Ai-skillsWrote 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/skills/codebygarv/ai-skills/fuzz-testing-designer)<a href="https://agentmods.dev/skills/codebygarv/ai-skills/fuzz-testing-designer"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/fuzz-testing-designer.svg" alt="Measured on agentmods" 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 | $0.00034 | $0.00416 |
| Opus 5 | $0.00017 | $0.00208 |
| Sonnet 5 | $0.00007 | $0.00083 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
fuzz-testing-designer 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 4d 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.
What it actually says
Purpose
Design coverage-guided fuzz testing harnesses and property-based tests (AFL, libFuzzer, Atheris, Go native testing.F, fast-check) that generate millions of pseudo-random, adversarial inputs to discover buffer overflows, unhandled panics, assertion failures, and infinite loops.
When to Use
- Testing data parsers (JSON, XML, YAML, binary protocols, image decoders).
- Validating cryptographic algorithms, compilers, and serialization engines.
- Securing untrusted user input handlers against malicious exploit payloads.
What to Analyze
- Fuzz Target Entry Point: Minimal, deterministic function signature accepting byte slices or structured objects.
- Seed Corpus: High-quality initial valid samples to guide mutation algorithms toward deeper code paths.
- Property Invariants: Assertions that must hold true for any input (e.g.
deserialize(serialize(x)) == x, no unhandled panics, execution completes in <100ms). - Sanitizers: AddressSanitizer (ASan), MemorySanitizer (MSan), and UndefinedBehaviorSanitizer (UBSan).
- Crash Minimization: Replay and minimization script for discovered failure artifacts.
Output Format
- Fuzz Test Harness Code: Complete test harness in Go (
F.Fuzz), TypeScript (fast-check), Python (Atheris), or Rust (cargo-fuzz). - Property Invariants Specification: Mathematical or logical invariants asserted.
- Corpus & Crash Reproducer Guide: Instructions to reproduce and minimize crashes.
Avoid
- Performing expensive disk I/O or network calls inside the inner fuzz loop (kills execution throughput).
- Fuzzing non-deterministic code containing random seeds or system timers.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 34 lines · 34 tokens per session scan A ea8c2cbf4c32
fuzz-testing-designer is a skill published in the GitHub repository codebygarv/Ai-skills (25 stars, last pushed 19d ago), licensed MIT. It adds 34 tokens to every session and 416 once invoked, about $0.0002 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 2026-09-03.
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