Skill audit report
Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
FAIL30
24 GitHub stars
Stars/forks activity
FAIL32
24 stars, 0 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
21d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
PASS86
Metadata includes enough usage and workflow context
Dependency/runtime risk
WARN56
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add typesafe-ai/skills --skill typesafe-ai
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/typesafe-ai/skills/tree/main/skills/typesafe-ai
Review status
WARN46
AI review approval is missing
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add typesafe-ai/skills --skill typesafe-ai
Repository
88
https://github.com/typesafe-ai/skills/tree/main/skills/typesafe-ai
License
86
MIT
Maintenance
100
21d 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
56
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
32
24 stars, 0 forks; issue activity unavailable in current metadata
Adoption
42
24 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.