Skill audit report
Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with fair-comparison caveats and no-overclaim summaries in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline execution, conservative training verification, default routing, verified SOTA claims, or implicit experimentation.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
484 GitHub stars
Stars/forks activity
WARN57
484 stars, 16 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
2d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add lllllllama/RigorPilot-Skills --skill explore-run
Install command safety
PASS92
standard package or runtime install path
Permission surface
INFO62
shell or command execution, filesystem or document access
Repository evidence
PASS86
https://github.com/lllllllama/RigorPilot-Skills/tree/main/skills/explore-run
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add lllllllama/RigorPilot-Skills --skill explore-run
Repository
88
https://github.com/lllllllama/RigorPilot-Skills/tree/main/skills/explore-run
License
86
MIT
Maintenance
100
2d since push
AI review
55
The skill depends on shared modules from the ai-research-reproduction skill (e.g., write_explore_bundle.py) which may not be present if the full RigorPilot skill set is not installed, potentially causing runtime errors.
Warnings
Method
This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.
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86
Usable description available
Dependency risk
90
no major dependency risk hints in public metadata
Install command safety
92
standard package or runtime install path
Permission surface
62
shell or command execution, filesystem or document access
Stars/forks activity
57
484 stars, 16 forks; issue activity unavailable in current metadata
Adoption
68
484 GitHub stars