Compare skills
Pick 2–4 skills and compare what really matters: fit, risk, install effort, and community signal.
Selected skills (2/4)
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
scholar-rag
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
ui-ux-pro-max
Execution risk：High
Threat tags：data exfiltration, human approval gap
Control gaps：missing license, network without allowlist, no human approval
| Dimension | scholar-rag | ui-ux-pro-max |
|---|---|---|
| SAS-v2.1 pre-install audit | ||
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | data exfiltration, human approval gap |
Control gaps | missing license, broad permissions, shell without guardrails | missing license, network without allowlist, no human approval |
Permission summary | Permission review, Network, Command | Network, Command |
Evidence confidence | 67% | 63% |
| Source & provenance | ||
Provenance | PangHu1020/scholar-rag | nextlevelbuilder/ui-ux-pro-max-skill/tree/main/.claude/skills/ui-ux-pro-max |
Category | Knowledge & RAG | Design & Content |
Freshness | 2026-04-06 | |
| Risk & trust | ||
Permission hints | repository clone, local runtime dependencies | registry access, remote metadata pull, runtime dependencies may be required |
| Install & compatibility | ||
Supported tools | Universal | Claude, Codex, Cursor, Universal |
Install method | script-backed | registry-install |
Install friction | 40 | |
| Community | ||
Stars | 22 | 29.8K |
Repository: OpenViking
Author: volcengine · Source status: Clear source
OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw).
Score basis：Clear source · Risk needs review · Universal
Repository: generative-ai-for-beginners-project-based-guide-to-building-rag-agents
Author: hereandnowai · Source status: Clear source
A beginner-friendly, project-driven tutorial on generative AI and LangChain agents.
Score basis：Clear source · Low risk signals · Universal
Repository: Buddy
Author: is-leeroy-jenkins · Source status: Clear source
An AI for federal financial management designed to support Financial Analysts, Managers, and Policy Professionals.
Score basis：Clear source · High risk signals · Universal
Repository: AI-QA-Retrieval-Assistant-API
Author: mvsaran · Source status: Clear source
A complete, end-to-end **Retrieval-Augmented Generation (RAG)** API server built with **Python**, **FastAPI**, **LangChain**, and **ChromaDB**.
Score basis：Clear source · Low risk signals · Universal
Repository: rag_demos
Author: dappros · Source status: Clear source
Examples of RAG (Retrieval-Augmented Generation) with Ethora, LangChain, and OpenAI.
Score basis：Clear source · Low risk signals · Universal
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