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
UI-TARS-desktop
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
pathway
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, memory context poisoning
Control gaps：missing license, broad permissions, shell without guardrails
playwright
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | UI-TARS-desktop | pathway | playwright |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 65 · Manual review | 65 · Manual review | 66 · Manual review |
Score basis | Clear source, High execution risk, Universal | Clear source, High execution risk, Universal | Clear source, High execution risk, Universal |
Execution risk | High | High | High |
Threat tags | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, memory context poisoning | 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, broad permissions, shell without guardrails |
Permission summary | Permission review, Network, Command | Permission review, Network, Command | Permission review, Network, Command |
Evidence completeness | 67% | 67% | 65% |
| Source & provenance | |||
Provenance | bytedance/UI-TARS-desktop | pathwaycom/pathway | microsoft/playwright |
Category | Web & Automation | Automation & Workflows | Automation & Workflows |
Freshness | |||
| Risk & permission signals | |||
Audit signals | No explicit signals | metadata-only | metadata-only |
Permission hints | repository clone, local runtime dependencies | repository clone | repository clone |
| Install & compatibility | |||
Supported tools | Universal | Universal | Universal |
Install method | script-backed | script-backed | script-backed |
Install friction | |||
| Community | |||
Stars | 29.3K | 63.5K | 86.4K |
Repository: pending
Author: Iván · Source status: Source needs review
Browser automation via Playwright MCP.
Score basis：Source needs review · High execution risk · Claude · Evidence completeness 69%
Repository: mcp-perf-suite
Author: canyonlabz · Source status: Clear source
A modular MCP server suite for performance‑testing workflows: generate JMeter scripts from browser automation, manage and run load tests, ingest and correlate metrics from APM tools using temporal correlation analysis, a
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: plaidify
Author: meetpandya27 · Source status: Clear source
Open-source API for authenticated web data extraction.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: scraper-mcp
Author: jessaminesimple608 · Source status: Clear source
🌐 Streamline web scraping with Scraper MCP, a server that optimizes content for AI by filtering data and reducing token usage for LLMs.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 69%
Repository: openclaw/skills
Author: hsyhph · Source status: Clear source
Automate web browser interactions using natural language via CLI commands.
Score basis：Clear source · High execution risk · Claude · Evidence completeness 69%
2026-03-27 |
2026-04-14 |
2026-04-14 |
40 |
75 |
75 |
