Demogpt
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 · Low risk signals · Universal
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
posthog
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
NVIDIA-Nemotron-3-Super
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
ArcGIS-JavaScript-AI-Component
Execution risk:High
Threat tags:unexpected code execution, identity privilege abuse, data exfiltration
Control gaps:missing license, broad permissions, shell without guardrails
| Dimension | posthog | NVIDIA-Nemotron-3-Super | ArcGIS-JavaScript-AI-Component |
|---|---|---|---|
| SAS-v2.1 pre-install audit | |||
Threat tags | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, identity privilege abuse, data exfiltration |
Permission summary | Permission review, Network, Command | Permission review, Network, Command | Permission review, Network, Secrets, Command |
Evidence confidence | 65% | 65% | 67% |
| Source & provenance | |||
Provenance | PostHog/posthog | cobusgreyling/NVIDIA-Nemotron-3-Super | ralouta/ArcGIS-JavaScript-AI-Component |
Freshness | 2026-04-07 | 2026-04-02 | 2026-03-30 |
| Risk & trust | |||
Trust score | 85 | 82 | 82 |
Audit signals | network access | No explicit signals | needs credentials |
| Install & compatibility | |||
Install friction | 40 | 40 | 55 |
| Community | |||
Stars | 32.4K | 26 | 4 |
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 · Risk needs review · Universal
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 · Low risk signals · Universal
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 · Low risk signals · Universal
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 · Low risk signals · Universal