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
skills-vote
Execution risk：High
Threat tags：unexpected code execution, data exfiltration, human approval gap
Control gaps：missing license, broad permissions, shell without guardrails
DemoGPT
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
claude-pace-maker
Execution risk：High
Threat tags：prompt injection, tool poisoning, unexpected code execution
Control gaps：missing license, broad permissions, shell without guardrails
| Dimension | skills-vote | DemoGPT | claude-pace-maker |
|---|---|---|---|
| SAS-v2.1 pre-install audit | |||
Threat tags | unexpected code execution, data exfiltration, human approval gap | prompt injection, tool poisoning, unexpected code execution | prompt injection, tool poisoning, unexpected code execution |
Evidence confidence | 65% | 67% | 68% |
| Source & provenance | |||
Provenance | MemTensor/skills-vote | melih-unsal/DemoGPT | LightspeedDMS/claude-pace-maker |
Freshness | 2026-04-08 | 2026-04-01 | 2026-04-06 |
| Risk & trust | |||
Trust score | 72 | 82 | 82 |
Audit signals | |||
| Community | |||
Stars | 17 | 1.9K | 4 |
Repository: entroly
Author: juyterman1000 · Source status: Clear source
Entroly helps AI coding tools like Cursor, Copilot, and Claude Code use the right context from your entire codebase—improving output quality while reducing token usage.
Score basis：Clear source · Risk needs review · Universal
Repository: NVIDIA-Nemotron-3-Super
Author: cobusgreyling · Source status: Clear source
Controllable reasoning demos for NVIDIA Nemotron 3 Super (120B/12B MoE) — chat UI, CLI, API server, tool calling, budget sweep, and adaptive routing Topics: gradio, llm, mixture-of-experts, moe, nemotron, nim, nvidia, re
Score basis：Clear source · Low risk signals · Universal
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
No explicit signals |
writes files |
