Agentic Ai Engineering
Repository: agentic-ai-engineering
Author: agenticloops-ai · Source status: Clear source
Hands-on tutorials for building AI agents from scratch.
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
logger
Execution risk:High
Threat tags:prompt injection, tool poisoning, unexpected code execution
Control gaps:missing license, broad permissions, shell without guardrails
rox
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
| Dimension | logger | rox | NVIDIA-Nemotron-3-Super |
|---|---|---|---|
| SAS-v2.1 pre-install audit | |||
Threat tags | prompt injection, tool poisoning, unexpected code execution | unexpected code execution, data exfiltration, human approval gap | unexpected code execution, data exfiltration, human approval gap |
Evidence confidence | 69% | 65% | 65% |
| Source & provenance | |||
Provenance | smol-ai/logger | BeWelcome/rox | cobusgreyling/NVIDIA-Nemotron-3-Super |
Freshness | 2024-03-28 | 2026-03-30 | 2026-04-02 |
| Risk & trust | |||
Trust score | 67 | 82 | 82 |
| Community | |||
Stars | 148 | 210 | 26 |
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: Claude-Code-Agent-Monitor
Author: hoangsonww · Source status: Clear source
A real-time monitoring dashboard for Claude Code agents, built with SQLite3, Node.js, Express, React, Vite, TailwindCSS, and WebSockets.
Score basis:Clear source · High risk signals · Universal
Repository: ultimate-prompt-engineering-playbook
Author: amerob · Source status: Clear source
A collection of 114 notebooks covering modern prompt engineering techniques.
Score basis:Clear source · Low risk signals · Universal