cortex
SolidML/AI engineer — LLM integrations, prompt engineering, model pipelines, evals, RAG.
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Quality Score: 97/100
Skill Content
Details
- Author
- jeremylongshore
- Repository
- jeremylongshore/claude-code-plugins-plus-skills
- Created
- 7 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
cortex-integrate
Design and implement an AI feature integration — model selection, architecture pattern, system prompt, data flow, error handling, cost estimate. Use when asked to "add AI to this", "LLM integration", "add Claude/GPT", or "AI-powered feature".
cortex-model
Build an ML pipeline — from data to trained model to serving endpoint. Use when asked to "build ML model", "train a model", "prediction pipeline", "classification", or "regression".
cortex-eval
Evaluate model performance — check for accuracy drops, data drift, and error patterns. Use when asked about "model accuracy dropped", "evaluate the model", "check for drift", or "model performance".
cortex-skills-loop
Drives the cortex skills recommend-feedback-rate loop. Use when a context change occurs (new file types, domain shift, task pivot) or when a task completes and skill effectiveness should be recorded.
cortex-prompt
Build a production-ready prompt package — system prompt, few-shot examples, output format, edge case handling, eval criteria. Use when asked to "prompt engineering", "build a prompt", "write a system prompt", or "improve this prompt".