Experiment Provenance
SkillMonitoring & opsCapture experiment provenance with reproducible run metadata, artifact pointers, and decision logs for scientific claims.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Experiment Provenance skill
What this skill tells your AI
The instructions your AI receives, as published by drpedapati/sciclaw in skills/experiment-provenance/SKILL.md and read by ahel’s review.
Use this skill when a task produces evidence that may become a manuscript claim.
When to use
- "track provenance"
- "log this experiment"
- "record reproducible run details"
- "capture evidence for manuscript claim"
Required provenance fields
- Objective and hypothesis.
- Exact command(s) executed.
- Input files, config, and environment assumptions.
- Output artifact paths.
- Validation status (tests/build/render).
- Claim boundary and uncertainty notes.
Workflow
- Record run intent before execution.
- Execute with deterministic commands where possible.
- Store output artifact paths, not just summaries.
- Link provenance notes to
plans/main-plan-activity.mdandplans/main-plan-log.csv. - Mark evidence quality: strong, partial, or insufficient.
Signals
- GitHub stars
- 88
- Forks
- 17
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
experiment-provenance- Source
- github.com/drpedapati/sciclaw