Github Openai Openai Cookbook
Repository: openai-cookbook
Author: openai · Source status: Clear source
Examples and guides for using the OpenAI API
Score basis:Clear source · High execution risk · Universal · Evidence completeness 65%
Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
Comparison matrix
Highlights show current best; tooltip explains diff/best rules.
Score-basis diff rules / risk tag notes
Start with the matrix. Open this section when you need to understand audit grades, top threats, control gaps, and best-value highlights.
Suggested baseline
Search to add skills, or paste 2–4 comma-separated slugs.
How differences are detected
A row is marked different when selected skills have distinct values. Only-differences mode hides rows that are identical.
How best values are highlighted
Pre-install score, evidence completeness, and community signal prefer higher values; execution risk and install friction prefer lower values.
How to read risk tags
Risk tags come from SAS-v2.1 public-evidence signals and point to command, network, secret, context, or supply-chain items to review before install.
Selected audit signals
CLIP
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
openai-python
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
openclaw-office
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
| Dimension | CLIP | openai-python | openclaw-office |
|---|---|---|---|
| Source & provenance | |||
Provenance | openai/CLIP | openai/openai-python | WW-AI-Lab/openclaw-office |
Category | Automation & Workflows | Automation & Workflows | Operations & Infra |
Freshness | 2026-03-26 | 2026-04-14 | 2026-04-07 |
| Risk & permission signals | |||
Audit signals | metadata-only | metadata-only | network access |
Permission hints | repository clone | repository clone | repository clone, local runtime dependencies |
| Install & compatibility | |||
Install friction | 75 | 75 | 40 |
| Community | |||
Stars | 33.2K | 30.5K | 513 |
Repository: whisper
Author: openai · Source status: Clear source
Robust Speech Recognition via Large-Scale Weak Supervision
Score basis:Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: FastChat
Author: lm-sys · Source status: Clear source
An open platform for training, serving, and evaluating large language models.
Score basis:Clear source · High execution risk · Universal · Evidence completeness 65%