Skill audit report
Multi-reviewer peer-review system for food & nutrition manuscripts. Simulates an editorial panel — a coordinating editor, three domain reviewers (methodology/statistics, domain/novelty, integrity/ethics), and a devil's advocate — plus a formatting-compliance check against the target journal (APA 7.0 by default, or a specific journal via journal-selector). Grounds the panel first: reads the manuscript's cited sources and the field's key literature into a knowledge base, so novelty and correctness are judged from evidence, not impression. Use for pre-submission review, reviewer reports, mock peer review, or a critique before submitting. Triggers: review my paper, peer review, referee report, reviewer reports, critique my manuscript, pre-submission review, is my paper ready, mock review, editorial review, assess novelty and rigor.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
WARN48
31 GitHub stars
Stars/forks activity
WARN43
31 stars, 3 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
22d 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 PangenomeAI/academic-skills-food-nutrition --skill food-review
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/PangenomeAI/academic-skills-food-nutrition/tree/main/food-review
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add PangenomeAI/academic-skills-food-nutrition --skill food-review
Repository
88
https://github.com/PangenomeAI/academic-skills-food-nutrition/tree/main/food-review
License
86
MIT
Maintenance
100
22d since push
AI review
55
Review approval is missing
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
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
43
31 stars, 3 forks; issue activity unavailable in current metadata
Adoption
42
31 GitHub stars
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.
Shell or command execution
highSkill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
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.
Database access
mediumSkill may inspect schemas, query databases, or work with persistent stores.