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arize-prompt-optimization

arize-ai/arize-skills

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.

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安装命令

npx skills add https://github.com/arize-ai/arize-skills --skill arize-prompt-optimization

SKILL.md

Arize Prompt Optimization Skill

SPACE — --space flags accept a space name (e.g., my-workspace) or a base64 space ID (e.g., U3BhY2U6...). Confirm a known name with ax spaces get NAME; ax spaces list is for human browsing.

Related skills

  • arize-prompts: Create, version, and label prompts in Prompt Hub with ax prompts (JSON messages, providers, labels such as production). Use that skill when the artifact should live in Arize; use arize-prompt-optimization below to improve prompt text from traces, datasets, and experiments.

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:

相关 Skills

arize-instrumentationarize-ai/arize-skillsAdds Arize AX tracing to an LLM application for the first time. Detects the stack, routes to the single matching integration doc, wires auto-instrumentation after user confirmation, and verifies traces land. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.数据与研究3492arize-tracearize-ai/arize-skillsDownloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.数据与研究3271arize-experimentarize-ai/arize-skillsCreates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A/B test models, or measure accuracy.智能体工作流3158arize-datasetarize-ai/arize-skillsCreates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.测试与安全3155arize-evaluatorarize-ai/arize-skillsHandles LLM-as-judge and code evaluator workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, code evaluator, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.智能体工作流3127arize-linkarize-ai/arize-skillsGenerates deep links to the Arize UI for projects, traces, spans, sessions, datasets, experiments, labeling queues, evaluators, and annotation configs. Discovers organization and project IDs with the ax CLI and produces clickable URLs for sharing Arize resources with team members. Use when the user wants to link to or open a project, trace, span, session, dataset, experiment, evaluator, or annotation config in the Arize UI.其他3093