Skill audit report
Use when the user has a results draft or a set of data-backed claims and wants each one adversarially verified against the underlying dataset before publishing — a pre-publication red-team of the findings. Extracts the discrete checkable claims from the draft, reproduces each claim's number against the data, stress-tests it against the threats most likely to kill it (outliers, confounds, Simpson's reversals, tiny subgroups, alternative specifications), and marks it verified, fragile, or refuted; fragile and refuted claims are revised — hedged, scoped, or retracted — until every claim is verified or appropriately qualified. The result is a draft where every surviving claim has been reproduced and survived a stress test. Not for open-ended discovery of new findings over a dataset (that is a data-analysis task), and not for diagnosing a single known anomaly or pipeline failure — this is a gate over an existing draft.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
163 GitHub stars
Stars/forks activity
WARN57
163 stars, 19 forks; issue activity unavailable in current metadata
Recent maintenance
PASS88
3mo since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO62
credential or environment access, external package install surface
Install availability
PASS92
npx skills add gaasher/Agent-Loop-Skills --skill claim-verify
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN60
secrets or environment access, filesystem or document access
Repository evidence
PASS86
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/claim-verify
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add gaasher/Agent-Loop-Skills --skill claim-verify
Repository
88
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/claim-verify
License
86
MIT
Maintenance
88
3mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
86
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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Usable description available
Dependency risk
62
credential or environment access, external package install surface
Install command safety
92
standard package or runtime install path
Permission surface
60
secrets or environment access, filesystem or document access
Stars/forks activity
57
163 stars, 19 forks; issue activity unavailable in current metadata
Adoption
68
163 GitHub stars
Financial decision safety
58
Research-only use: do not treat output as financial advice or execute a position without human approval.
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
Network access
mediumSkill likely fetches remote pages, APIs, repositories, or external services.
Filesystem access
mediumSkill may read or write project files, documents, generated artifacts, or local workspace state.
Secrets or environment access
highSkill metadata references credentials, tokens, environment variables, or secret-bearing workflows.