Venue Evidence Audit
SkillDev toolsAudit recent high-relevance papers from a target venue to identify claim-relevant experimental evidence gaps after core P0 results exist. Use for venue completeness and reviewer-risk analysis; not for redefining the research question or running experiments.
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 Venue Evidence Audit skill
What this skill tells your AI
The instructions your AI receives, as published by cpt13-g/build-research-evidence in .agents/skills/venue-evidence-audit/SKILL.md and read by ahel’s review.
Run only when the Orchestrator authorizes the audit and P0 is substantially complete. Read research/research_state.yaml, the current Claim-Evidence status, docs/PROTOCOLS.md, docs/ROLE_HANDOFFS.md, and docs/EVIDENCE_COMPLETION_PROTOCOL.md.
Analyze 5-10 recent, highly relevant papers, prioritizing same task, research question, method class, venue and recency. Record search date, sources, relevance, inclusion/exclusion reasons and uncertainty. Stop once core expectations, material gaps and high-ROI actions are stable; do not expand into a systematic review. Compare datasets, baselines, metrics, seed/statistical practice, ablations, sensitivity, robustness, generalization, efficiency, complexity, qualitative analysis and figure/table conventions.
Produce an Evidence Gap Matrix with current status, venue frequency, Claim relevance, reviewer risk, estimated cost, information gain and recommended priority. Recommendations do not enter the queue automatically. A common but Claim-irrelevant experiment is P3/SKIP. Do not alter the Research Spine, Primary Claims or Method, and report any positioning concern only as risk.
Signals
- GitHub stars
- 20
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
venue-evidence-audit- Source
- github.com/cpt13-g/build-research-evidence