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 agentmods add skills/ash1794/vibe-engineering/fuzz-parser-inputsnpx skills add ash1794/vibe-engineering --skill fuzz-parser-inputsgit clone --depth 1 https://github.com/ash1794/vibe-engineeringWhat 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 | $0.00042 | $0.00695 |
| Opus 5 | $0.00021 | $0.00347 |
| Sonnet 5 | $0.00008 | $0.00139 |
| Haiku 4.5 | $0.00004 | $0.00069 |
Grade A, and why
vibe-fuzz-parser-inputs 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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- vibe-fuzz-parser-inputs — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
vibe-fuzz-parser-inputs
Every parser will eventually see input you didn't expect. Fuzz testing finds the crashes before production does.
When to Use This Skill
- Implementing any parser (YAML, JSON, XML, config, DSL)
- Processing user-supplied input
- Handling webhook payloads or API responses
- Parsing file formats
When NOT to Use This Skill
- The parser is a well-tested standard library (e.g.,
encoding/json) - You're only reading known, controlled input
- The parser is trivial (e.g., splitting a string by comma)
Steps
Go Fuzz Tests
-
Create fuzz test file (
parser_fuzz_test.go):func FuzzParseConfig(f *testing.F) { // Seed corpus from existing test fixtures files, _ := filepath.Glob("testdata/*.yaml") for _, file := range files { data, _ := os.ReadFile(file) f.Add(data) } // Add targeted seeds f.Add([]byte("")) // empty f.Add([]byte("{}")) // minimal valid f.Add([]byte("\x00\x00")) // binary f.Fuzz(func(t *testing.T, data []byte) { // Should never panic result, err := ParseConfig(data) if err != nil { return // errors are fine } // If no error, result should be valid if result.Name == "" { t.Error("parsed successfully but Name is empty") } }) } -
Seed the corpus from:
- Existing test fixtures
- Real production examples
- Known edge cases
- Minimally valid inputs
- Binary/garbage data
-
Run initial fuzz:
go test -fuzz=FuzzParseConfig -fuzztime=30s -
Record results:
- Crashes found
- New corpus entries generated
- Edge cases discovered
-
Fix crashes -- Every panic or unexpected behavior becomes a permanent test case
Other Languages
- JavaScript/TypeScript: Use
jest-fuzzorfast-checkproperty-based testing - Python: Use
hypothesisfor property-based testing - Rust: Use
cargo-fuzzwithlibfuzzer
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.
- 2d ago First seen · 97 lines · 42 tokens per session scan A ca7b2689204c
vibe-fuzz-parser-inputs is a skill published in the GitHub repository ash1794/vibe-engineering (10 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 695 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 2026-08-31.
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