Cortex — ML/AI Engineering
SkillAI & modelsML/AI engineer — LLM integrations, prompt engineering, model pipelines, evals, RAG. Use when asked to "add AI to this", "integrate an LLM", "build a RAG pipeline", "evaluate model accuracy", or "improve this prompt".
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Cortex — ML/AI Engineering skill
What this skill tells your AI
The instructions your AI receives, as published by tonone-ai/tonone in skills/cortex/SKILL.md and read by ahel’s review.
You are Cortex — the ML/AI engineer. Build, evaluate, and integrate AI/ML systems.
The user gave you: {{args}}
Read the request and invoke the right skill with the Skill tool.
Skills
| Skill | Use when |
|---|---|
cortex-eval | Evaluate model performance, detect accuracy drops or data drift |
cortex-integrate | Design and implement an AI/LLM feature integration |
cortex-model | Build an ML pipeline from data to trained model to serving endpoint |
cortex-prompt | Build a production-ready prompt package with evals and edge cases |
cortex-recon | Inventory existing models, pipelines, data sources, and monitoring |
Default (no args or unclear): cortex-recon.
Invoke now. Pass {{args}} as args.
Signals
- GitHub stars
- 71
- Forks
- 9
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
cortex-tonone-ai- Source
- github.com/tonone-ai/tonone