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
Repository: playwright-python
Author: microsoft · Source status: Clear source
Python version of the Playwright testing and automation library.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
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
mcp-for-beginners
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
Openclaw Smart Search
Execution risk：High
Threat tags：unexpected code execution, identity privilege abuse, data exfiltration
Control gaps：missing license, broad permissions, shell without guardrails
Commitment Ready. 承诺。Compromiso.
Execution risk：High
Threat tags：unexpected code execution, identity privilege abuse, data exfiltration
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | mcp-for-beginners | Openclaw Smart Search | Commitment Ready. 承诺。Compromiso. |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 85 · Manual review | 85 · Evidence missing | 85 · Manual review |
Score basis | Clear source, High execution risk, Universal | Clear source, High execution risk, OpenClaw | Clear source, High execution risk, Claude |
Threat tags | unexpected code execution, data exfiltration, memory context poisoning | unexpected code execution, identity privilege abuse, data exfiltration | unexpected code execution, identity privilege abuse, data exfiltration |
Permission summary | Permission review, Network, Command | Permission review, Network, Secrets, Command | Permission review, Network, Secrets, Command |
Evidence completeness | 67% | 69% | 67% |
| Source & provenance | |||
Provenance | microsoft/mcp-for-beginners | openclaw/skills | openclaw/skills |
Category | Dev & Engineering | Integrations & Connectors | Design & Content |
Freshness | |||
| Risk & permission signals | |||
Audit signals | No explicit signals | needs credentials, network access, runs shell, writes files | needs credentials, network access, runs shell, writes files |
Permission hints | repository clone, local runtime dependencies | verify source provenance before install | verify source provenance before install |
| Install & compatibility | |||
Supported tools | Universal | OpenClaw | Claude, OpenClaw |
Install friction | 40 | 65 | 65 |
| Community | |||
Stars | 15.8K | 0 | 0 |
Repository: RD-Agent
Author: microsoft · Source status: Clear source
Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: playwright-dotnet
Author: microsoft · Source status: Clear source
.NET version of the Playwright testing and automation library.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: playwright-java
Author: microsoft · Source status: Clear source
Java version of the Playwright testing and automation library
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: edgeai-for-beginners
Author: microsoft · Source status: Clear source
This course is designed to guide beginners through the exciting world of Edge AI, covering fundamental concepts, popular models, inference techniques, device-specific applications, model optimization, and the developmen…
Score basis：Clear source · High execution risk · Universal · Evidence completeness 65%
Repository: MInference
Author: microsoft · Source status: Clear source
[NeurIPS'24 Spotlight, ICLR'25, ICML'25] To speed up Long-context LLMs' inference, approximate and dynamic sparse calculate the attention, which reduces inference latency by up to 10x for pre-filling on an A100 while ma…
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
2026-04-08 |
2026-03-26 |
2026-04-01 |
