CLIP
Repository: CLIP
Author: openai · Source status: Clear source
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Score basis:Clear source · Risk needs review · Universal
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.
SAS-v2.1 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
Audit score, evidence confidence, trust score, 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
human-eval
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
database-migration
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
openai-cookbook
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
| Dimension | human-eval | database-migration | openai-cookbook |
|---|---|---|---|
| Source & provenance | |||
Provenance | openai/human-eval | wshobson/agents | openai/openai-cookbook |
Category | Automation & Workflows | Data & Analytics | Automation & Workflows |
Freshness | 2025-01-18 | 2026-04-09 | 2026-04-14 |
| Risk & trust | |||
Trust score | 92 | 82 | 92 |
Audit signals | |||
| Install & compatibility | |||
Supported tools | Universal | Claude, Codex, Cursor, Windsurf | Universal |
Install method | script-backed | instruction-only | script-backed |
Install friction | |||
| Community | |||
Stars | 3.2K | 33.2K | 72.7K |
Repository: llm-course
Author: mlabonne · Source status: Clear source
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Score basis:Clear source · Risk needs review · Universal
runs shell |
metadata-only |
Permission hints | repository clone | local skill installation, workspace file updates | repository clone |
|---|
75 |
70 |
75 |