Skill audit report
The engineering loop - select, advance, distill, deliver - for running a work session on a project. Invoke when STARTING a session or picking the next thing to work on; sizing a unit of work or matching it to your model tier; running long/autonomously and deciding pace or when to stop; deciding where a learning should live (lesson vs memory vs project-level skill); or wrapping up a unit/session (commit, report, handoff note).
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
239 GitHub stars
Stars/forks activity
WARN57
239 stars, 32 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
PASS90
no major dependency risk hints in public metadata
Install availability
PASS92
npx skills add telagod/code-abyss --skill loop-engineering
Install command safety
PASS92
standard package or runtime install path
Permission surface
PASS100
no high-risk permission surface in public metadata
Repository evidence
PASS86
https://github.com/telagod/code-abyss/tree/main/skills/_kernel/loop-engineering
Review status
PASS88
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add telagod/code-abyss --skill loop-engineering
Repository
88
https://github.com/telagod/code-abyss/tree/main/skills/_kernel/loop-engineering
License
86
MIT
Maintenance
88
2mo since push
AI review
88
Approved with no listed issues
README/SKILL.md completeness
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
100
no high-risk permission surface in public metadata
Stars/forks activity
57
239 stars, 32 forks; issue activity unavailable in current metadata
Adoption
68
239 GitHub stars
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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