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Keep local training dataset provenance, merged outputs, and manifest truth aligned across dataset-building repos. Use when teacher distillation, enrichment exports, or study manifests change together.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Run the local NullClaw host security app for skill governance, curated-source discovery, guarded threat suppression, and self-governance on Windows hosts.
Sweep one or more local repositories for implementation gaps and produce deterministic, evidence-backed remediation lanes. Use when you need cross-repo detection of missing tests, docs lockstep drift, risky TODO/FIXME additions, and release-hygiene misses.
Build and query bounded metadata-only repository indexes without rg process churn. Use when working in very large repos and you need deterministic file discovery by path, extension, language, scope, or freshness.
Detect recent cross-repo work and produce deterministic JSON evidence for skill curation and routing decisions. Use when workflows span multiple repos and you need a bounded view of recent commits, touched files, and policy/contract-sensitive changes.
Enforce hardware-first diagnosis and fixes in <PRIVATE_REPO_B>. Use for runtime probe, telemetry, inference, and integration failures where strict real-hardware behavior, no new stubs, deterministic diagnostics, and no unrequested driver/runtime mutation are required.
Run a defender-first security sweep on code, configs, prompts, model/tooling surfaces, or third-party contribution lanes. Use when a request involves safe bug, leak, zero-day-class, exploit, or hack hunting for protection, when contributing to outside repositories and you want a focused security pass, or when touching auth, secrets, permissions, network exposure, prompt/tool boundaries, data flow, or update/build surfaces. This skill is defensive only and must never be used for weaponization or unauthorized access.
| name | dataset-provenance-manifest-governance |
| description | Keep local training dataset provenance, merged outputs, and manifest truth aligned across dataset-building repos. Use when teacher distillation, enrichment exports, or study manifests change together. |
Use this skill when the Penny training-data chain changes across Qwen Training and Media Workbench surfaces.
$qwen-training-dataset-factory$qwen-training-campaign-ops$media-workbench-indexing-governance$docs-alignment-lockUse this skill only for dataset provenance, manifest lineage, and derived training-artifact governance.
For checkpoint evaluation or fine-tune execution, route through the more specific training skills.