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testland/corpus-management-reference

Pure-reference catalog of fuzz-corpus management practices. Defines what a corpus is (seed corpus + evolved corpus saved by the fuzzer), corpus directory layout per libFuzzer / AFL++ / Go native / cargo-fuzz / OSS-Fuzz, the canonical crash-artefact naming (crash-{sha1} / leak-{sha1} / timeout-{sha1}), seed corpus construction strategies (sample-from-prod, sample-from-test-fixtures, from-spec-keywords), corpus minimisation, dictionary files, and the OSS-Fuzz integration corpus sync. Use as the corpus-discipline reference when building a fuzz target or maintaining a long-running fuzz campaign.

76

Quality

95%

Does it follow best practices?

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SecuritybySnyk

Passed

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Overview
Quality
Evals
Security
Files

Quality

Content

87%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-organized, actionable reference catalog with executable commands and tight prose. The only weakness is workflow clarity: the main multi-step workflow (crash handling) lacks an explicit validation checkpoint and error-recovery feedback loop.

Suggestions

Add an explicit error-recovery branch to the crash-artefact handling workflow, e.g. 'If the crash does not reproduce, rerun against the binary revision that found it and verify sanitiser flags match' before minimising.

Add a verification checkpoint after corpus minimisation, e.g. rerun the fuzzer briefly against the minimised corpus to confirm coverage is preserved before discarding the original corpus.

DimensionReasoningScore

Conciseness

A lean reference catalog built from tables, directory layouts, and executable snippets that assumes Claude's competence and avoids explaining fuzzing basics; every section earns its place.

3 / 3

Actionability

Provides copy-paste-ready, executable guidance throughout — per-fuzzer invocations, minimisation commands, dictionary usage, and CI YAML — with concrete directory layouts and crash-handling steps.

3 / 3

Workflow Clarity

The crash-artefact handling section is a clear numbered sequence, but its validation step (reproduce locally) is implicit and there is no error-recovery feedback loop for when reproduction or minimisation fails.

2 / 3

Progressive Disclosure

No bundle files exist, so the self-contained single-file reference is judged on organization; sections are clearly headed and a References section signals external docs with no nested or broken references.

3 / 3

Total

11

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12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, information-dense description that names concrete capabilities, includes an explicit use-when trigger, and carves out a distinct niche. It uses third-person/imperative voice and avoids fluff, though it is long.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities — corpus directory layout per fuzzer, crash-artefact naming (crash-{sha1}/leak-{sha1}/timeout-{sha1}), seed construction strategies, minimisation, dictionary files, and OSS-Fuzz sync — rather than vague language.

3 / 3

Completeness

Clearly answers both what (defines corpus components, layouts, naming, strategies, minimisation, dictionaries, sync) and when ('Use as the corpus-discipline reference when building a fuzz target or maintaining a long-running fuzz campaign').

3 / 3

Trigger Term Quality

Contains natural domain terms a user would actually say when needing this skill — 'fuzz target', 'fuzz campaign', 'seed corpus', 'corpus' — alongside the specific fuzzer names.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear, narrow niche (fuzz-corpus management) and is explicitly a pure-reference catalog consumed by per-language fuzzer skills, making conflict with unrelated skills unlikely.

3 / 3

Total

12

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12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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