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arize-prompt-optimization

Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.

skills/arize-prompt-optimization/SKILL.md

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# Arize Prompt Optimization Skill

> **`SPACE`** — All `--space` flags and the `ARIZE_SPACE` env var accept a space **name** (e.g., `my-workspace`) or a base64 space **ID** (e.g., `U3BhY2U6...`). Find yours with `ax spaces list`.

## Concepts

### Where Prompts Live in Trace Data

LLM applications emit spans following OpenInference semantic conventions. Prompts are stored in different span attributes depending on the span kind and instrumentation:

| Column | What it contains | When to use |
|--------|-----------------|-------------|
| `attributes.llm.input_messages` | Structured chat messages (system, user, assistant, tool) in role-based format | **Primary source** for chat-based LLM prompts |
| `attributes.llm.input_messages.roles` | Array of roles: `system`, `user`, `assistant`, `tool` | Extract individual message roles |