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Fuzz Harness Builder

ASecurity

Use when creating, adapting, reviewing, or debugging JS/TS fuzzers, corpus fixtures, replay files, shrinkers, repro writers, or deterministic random test harnesses.

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  • Added September 12, 2026
researchdebuggingapi

Works with

  • api

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Scanned September 12, 2026

npx -y skills add siliconjungle/-shapeshift-labs-evidence-kit --skill fuzz-harness-builder --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: fuzz-harness-builder
description: Use when creating, adapting, reviewing, or debugging JS/TS fuzzers, corpus fixtures, replay files, shrinkers, repro writers, or deterministic random test harnesses.
---

# Fuzz Harness Builder

Fuzzers should produce useful failures, not just random load.

## Required Properties

- Deterministic seed: `--seed`.
- Bounded run size: `--cases`, and target-specific caps where needed.
- Replayable failure: `--replay` or `--write-repro`.
- Stable oracle: compare against a target-owned contract from docs, tests, source, or fetched material.
- Corpus promotion path: failures become checked-in fixture cases.
- Source traceability: corpus ideas from external projects cite the source-pass note or fetch manifest.

## Workflow

1. Identify the contract from the target project.
2. Generate valid values first, then mutate them according to the target contract.
3. Add or adapt a template:

```sh
npx evidence-kit add-fuzzer --name core --language js
```

4. Replace `runSubject()` with the project API under test.
5. On failure, write a reduced JSON repro and add it to the corpus.
6. When fuzzing ideas come from external sources, run `npm run research:list` and cite the matching source note.

## Reporting

Final reports should include command, seed, cases, any replay path, and whether corpus fixtures were added.

Files in this skill

  • SKILL.md1.3 KB
  • agents/openai.yaml215 B

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