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
codex-agentic-patterns
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, human approval gap
Control gaps:missing license, broad permissions, shell without guardrails
adc
Execution risk:High
Threat tags:prompt injection, tool poisoning, unexpected code execution
Control gaps:missing license, broad permissions, shell without guardrails
mcp-for-beginners
Execution risk:High
Threat tags:unexpected code execution, data exfiltration, memory context poisoning
Control gaps:missing license, broad permissions, shell without guardrails
| Dimension | codex-agentic-patterns | adc | mcp-for-beginners |
|---|---|---|---|
| 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, memory context poisoning |
Evidence confidence | 65% | 67% | 67% |
| Source & provenance | |||
Provenance | artvandelay/codex-agentic-patterns | iannelsondev/adc | microsoft/mcp-for-beginners |
Freshness | 2026-04-02 | 2026-04-02 | 2026-04-08 |
| Risk & trust | |||
Trust score | 72 | 82 | 85 |
Permission hints | repository clone, local runtime dependencies | local runtime dependencies, repository clone | repository clone, local runtime dependencies |
| Community | |||
Stars | 37 | 2 | 15.8K |
Repository: splitrail
Author: Piebald-AI · Source status: Clear source
Fast, cross-platform, real-time token usage tracker and cost monitor for Gemini CLI / Claude Code / Codex CLI / Qwen Code / Cline / Roo Code / Kilo Code / GitHub Copilot / OpenCode / Pi Agent / Piebald.
Score basis:Clear source · Risk needs review · Universal
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: tokscale
Author: junhoyeo · Source status: Clear source
🛰️ A CLI tool for tracking token usage from OpenCode, Claude Code, 🦞OpenClaw (Clawdbot/Moltbot), Pi, Codex, Gemini, Cursor, AmpCode, Factory Droid, Kimi, and more!
Score basis:Clear source · Risk needs review · Universal