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: DemoGPT
Author: melih-unsal · Source status: Clear source
🤖 Everything you need to create an LLM Agent—tools, prompts, frameworks, and models—all in one place.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
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
posthog
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
tool_calling_api
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
Icebreaker Openers. 破冰。Rompehielos.
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | posthog | tool_calling_api | Icebreaker Openers. 破冰。Rompehielos. |
|---|---|---|---|
| Pre-install decision | |||
Pre-install score | 85 · Manual review | 82 · Manual review | 85 · Evidence missing |
Score basis | Clear source, High execution risk, Universal | Clear source, High execution risk, Universal | Clear source, High execution risk, Claude |
Execution risk | High | High | High |
Threat tags | unexpected code execution, data exfiltration, human approval gap | prompt injection, tool poisoning, unexpected code execution | prompt injection, tool poisoning, unexpected code execution |
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, Secrets, Command |
Evidence completeness | 65% | 67% | 69% |
| Source & provenance | |||
Provenance | PostHog/posthog | Shuyib/tool_calling_api | openclaw/skills |
Category | Dev & Engineering | Dev & Engineering | Integrations & Connectors |
Freshness | |||
| Risk & permission signals | |||
Audit signals | network access | No explicit signals | needs credentials, network access, runs shell, writes files |
Permission hints | repository clone, local runtime dependencies | repository clone, local runtime dependencies | verify source provenance before install |
| Install & compatibility | |||
Supported tools | Universal | Universal | Claude, OpenClaw |
Install method | script-backed | script-backed | script-backed |
Install friction | |||
| Community | |||
Stars | 32.4K | 20 | 0 |
Repository: OpenTokenMonitor
Author: Hitheshkaranth · Source status: Clear source
OpenTokenMonitor is a lightweight, local-first desktop widget for tracking AI CLI usage across Claude, Codex, and Gemini.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: Promet
Author: Tripadh · Source status: Clear source
Promet is an AI-powered prompt engineering and optimization platform that helps users generate, refine, and evaluate high-quality prompts for better AI outputs.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: ArcGIS-JavaScript-AI-Component
Author: ralouta · Source status: Clear source
A production-style demo showcasing how to combine ArcGIS Maps SDK, ArcGIS Assistant agents, and a custom LangGraph agent for natural language map interaction and automated feature layer creation in ArcGIS Online or Enter
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: mcp-for-beginners
Author: microsoft · Source status: Clear source
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
Repository: raptor
Author: gadievron · Source status: Clear source
Raptor turns Claude Code into a general-purpose AI offensive/defensive security agent.
Score basis：Clear source · High execution risk · Universal · Evidence completeness 67%
2026-04-07 |
2026-03-28 |
2026-04-01 |
40 |
40 |
65 |
