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.
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
agentlego
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
agentic-ai-engineering
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
OpenAOE
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | agentlego | agentic-ai-engineering | OpenAOE |
|---|---|---|---|
| SAS-v2.1 pre-install audit | |||
Threat tags | unexpected code execution, data exfiltration, human approval gap | prompt injection, tool poisoning, unexpected code execution | unexpected code execution, data exfiltration, human approval gap |
Evidence confidence | 65% | 68% | 65% |
| Source & provenance | |||
Provenance | InternLM/agentlego | agenticloops-ai/agentic-ai-engineering | InternLM/OpenAOE |
Category | Dev & Engineering | Dev & Engineering | Automation & Workflows |
Freshness | |||
| Risk & trust | |||
Trust score | 60 | 82 | 90 |
Audit signals | No explicit signals | No explicit signals | metadata-only |
| Install & compatibility | |||
Install friction | 40 | 40 | 75 |
| Community | |||
Stars | 411 | 49 | 322 |
Repository: tool_calling_api
Author: Shuyib · Source status: Clear source
This project demonstrates function-calling with Python and Ollama, utilizing the Africa's Talking API to send airtime and messages to phone numbers using natural language prompts.
Score basis：Clear source · Low risk signals · Universal
Repository: claude-ide-tools
Author: YousifAshwal · Source status: Clear source
🛠️ Enhance Claude Code CLI’s refactoring with JetBrains IDEs, leveraging advanced semantic analysis for smarter code usage handling.
Score basis：Clear source · Low risk signals · Universal
Repository: HuixiangDou
Author: InternLM · Source status: Clear source
HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance
Score basis：Clear source · Risk needs review · Universal
2024-09-13 |
2026-04-07 |
2025-06-19 |
Permission hints |
|---|
repository clone, local runtime dependencies |
repository clone, local runtime dependencies |
repository clone |
