Skill audit report
Use when the user wants to generate and literature-vet a pool of novel, testable research hypotheses for a question or domain. A multi-agent loop: a Generator proposes candidate hypotheses, a LiteratureScout grounds each in real retrieved literature (already known? closest prior work? what gap does it fill?), and a Judge scores them against a fixed rubric and keeps the strong, non-duplicate ones; rounds repeat — mutating toward the open gaps — until fresh rounds stop adding keepers. Not for sharpening or decomposing a research question (no grounding/scoring there), and not for grading an existing written proposal against the literature.
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
2mo since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
INFO64
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add gaasher/Agent-Loop-Skills --skill hypothesis-gen
Install command safety
PASS92
standard package or runtime install path
Permission surface
FAIL34
secrets or environment access, filesystem or document access
Repository evidence
PASS86
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/hypothesis-gen
Review status
INFO66
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 hypothesis-gen
Repository
88
https://github.com/gaasher/Agent-Loop-Skills/tree/main/loops/hypothesis-gen
License
86
MIT
Maintenance
88
2mo since push
AI review
55
The skill depends on a sibling 'literature-search' skill; if missing, it degrades to web search, but the setup instructions could be clearer about installation steps.
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
64
credential or environment access, network or browser surface
Install command safety
92
standard package or runtime install path
Permission surface
34
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.
Database access
mediumSkill may inspect schemas, query databases, or work with persistent stores.