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-shapeshift-labs-evidence-kit
-shapeshift-labs-evidence-kit enthält 7 gesammelte Skills von siliconjungle, mit Repository-Berufsabdeckung und Skill-Detailseiten auf SkillsMP.
Skills in diesem Repository
Use when adding ShapeShift Labs Evidence Kit to a JS/TS project, initializing the full tests/fuzzers/benchmarks/package-boundary/perf-wiki harness, or helping an AI agent establish maximum evidence coverage in another repository.
Use when creating, adapting, reviewing, or debugging JS/TS fuzzers, corpus fixtures, replay files, shrinkers, repro writers, or deterministic random test harnesses.
Use when mining external JS/TS libraries, runtimes, papers, benchmark suites, bug corpora, or production systems for ideas that should become local tests, fuzzers, benchmarks, or evidence notes.
Use when adapting ShapeShift Labs Evidence Kit to a specific JS/TS project by deriving target-owned source lists, correctness contracts, corpus cases, fuzz generators, benchmark fixtures, source-pass plans, or evidence acceptance criteria from that project's own code, docs, tests, issues, or fetched sources.
Use for JS/TS performance-sensitive changes, benchmark additions, benchmark regressions, benchmark result JSON, or any claim that code is faster, smaller, cheaper, or not slower.
Use when changing JS/TS package exports, startup/import cost, package size, public subpaths, dependency direction, optional peers, tree-shaking, or package-boundary tests.
Use when creating or updating JS/TS performance evidence notes, iteration logs, research notes, generated docs/perf indexes, or searchable benchmark/result summaries.