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
playwright-python
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
mcpcan
Execution risk：High
Threat tags：unexpected code execution, identity privilege abuse, data exfiltration
Control gaps：missing license, broad permissions, shell without guardrails
Config Rollback
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, shell without guardrails, network without allowlist
| Dimension | playwright-python | mcpcan | Config Rollback |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 66 · Manual review | 63 · Manual review | 69 · Manual review |
Score basis | Clear source, High execution risk, Universal | Clear source, High execution risk, Universal | Clear source, High execution risk, OpenClaw |
Execution risk | High | High | High |
Threat tags | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, identity privilege abuse, data exfiltration | unexpected code execution, data exfiltration, human approval gap |
Control gaps | missing license, broad permissions, shell without guardrails | missing license, broad permissions, shell without guardrails | missing license, shell without guardrails, network without allowlist |
Permission summary | Permission review, Network, Command | Permission review, Network, Secrets, Command | Permission review, Network, Command |
Evidence completeness | 65% | 67% | 63% |
| Source & provenance | |||
Provenance | microsoft/playwright-python | Kymo-MCP/mcpcan | openclaw/skills |
Category | Automation & Workflows | Operations & Infra | Operations & Infra |
Freshness | |||
| Risk & permission signals | |||
Audit signals | metadata-only | needs credentials, network access | runs shell |
Permission hints | repository clone | repository clone, local runtime dependencies | verify source provenance before install |
| Install & compatibility | |||
Supported tools | Universal | Universal | OpenClaw |
Install method | script-backed | script-backed | script-backed |
Install friction | |||
| Community | |||
Stars | 14.5K | 717 | 0 |
Repository: semantic-kernel
Author: microsoft · Source status: Clear source
Integrate cutting-edge LLM technology quickly and easily into your apps
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: graphrag
Author: microsoft · Source status: Clear source
A modular graph-based Retrieval-Augmented Generation (RAG) system
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: langextract
Author: google · Source status: Clear source
A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: openai-python
Author: openai · Source status: Clear source
The official Python library for the OpenAI API
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
2026-03-27 |
2026-04-03 |
2026-02-28 |
75 |
55 |
50 |
