rseng-provenance
SolidCovers capturing and packaging the provenance of software and data: which inputs, code versions, parameters, environments and agents produced each result, recorded run by run; the W3C PROV model for describing it, RO-Crate for packaging research objects with their provenance, embedding provenance in file metadata, and data-flow lineage across pipelines. Use when the user asks where a result came from or whether it can be traced, wants provenance capture, lineage or an RO-Crate, or mentions PROV, research objects or audit trails; use PROACTIVELY when a pipeline produces results whose origins must be reconstructable long after the run.
Install
Quality Score: 83/100
Skill Content
Details
- Author
- fdiblen
- Repository
- fdiblen/rseng-agent-skills
- Created
- 4 days ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
rseng-reproducibility
Covers end-to-end computational reproducibility: making a project's results regenerable with one command, determinism and seed discipline, research compendium structure, replication packages for papers, Binder-launchable repositories, artifact evaluation and reproducibility badges. Use PROACTIVELY when the user wants results others can reproduce, prepares a replication package or artifact submission, mentions reproducibility, research compendia, Binder or badges, asks why results differ between runs or machines, or is about to publish results whose regeneration path is untested. (Pinning environments: rseng-reproducible-environments; pipeline automation: rseng-workflows; run-level lineage: rseng-provenance.)
provenance
收集系统全链路操作日志,生成可追溯的执行证据链与向量索引,是多智能体系统可观测性与安全审计的底座。
antinet-provenance
软件开发工程师与信息安全分析师在构建多智能体系统时,当需全链路可观测与安全审计,请用此技能。它自动收集操作日志,生成可追溯证据链与向量索引,开箱即用实现系统审计与精准回放,让Agent运行安全透明。