Skill audit report
Applies the reasoning, principles, and frameworks of Andrew Ng (machine learning pioneer, co-founder of Coursera and DeepLearning.AI, Stanford University, and former Google Brain lead). Use this skill whenever the user is navigating AI application development, agentic workflows, automation strategy, AI-native software engineering, or rapid prototyping. Trigger this skill when discussing career advice in the AI era, evaluating AI regulations, structuring machine learning projects, or deciding how to integrate AI into a business. It emphasizes task-based automation, data-centric ML, and driving the cost of proof-of-concepts to zero.
OpenAgentSkill Trust Score
The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.
GitHub adoption
INFO62
122 GitHub stars
Stars/forks activity
WARN57
122 stars, 18 forks; issue activity unavailable in current metadata
Recent maintenance
PASS100
29d since push
License clarity
PASS86
MIT
README/SKILL.md completeness
INFO76
Public metadata needs stronger README/SKILL.md context
Dependency/runtime risk
INFO64
credential or environment access, network or browser surface
Install availability
PASS92
npx skills add K-Dense-AI/mimeographs --skill andrew-ng
Install command safety
PASS92
standard package or runtime install path
Permission surface
WARN60
secrets or environment access, network or browser access
Repository evidence
PASS86
https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/andrew-ng
Review status
INFO66
AI review data available
Agent Proven outcomes
INFO54
No agent outcome data yet
Checks
Install path
92
npx skills add K-Dense-AI/mimeographs --skill andrew-ng
Repository
88
https://github.com/K-Dense-AI/mimeographs/tree/main/mimeographs/andrew-ng
License
86
MIT
Maintenance
100
29d since push
AI review
55
The SKILL.md contains some duplication between core principles, mental models, and anti-patterns (e.g., the electric motor analogy appears multiple times), which could be streamlined to reduce context bloat.
README/SKILL.md completeness
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
60
secrets or environment access, network or browser access
Stars/forks activity
57
122 stars, 18 forks; issue activity unavailable in current metadata
Adoption
68
122 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.
Network access
mediumSkill likely fetches remote pages, APIs, repositories, or external services.
Secrets or environment access
highSkill metadata references credentials, tokens, environment variables, or secret-bearing workflows.