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arize-ai

arize-ai

8 Skills published on GitHub.

phoenix-frontend

Frontend development guidelines for the Phoenix AI observability platform. Use when writing, reviewing, or modifying React components, TypeScript code, styles, or UI features in the app/ directory. Triggers on any frontend task — new components, UI changes, styling, accessibility fixes, form handling, or component refactoring. Also use when the user asks about frontend conventions or component patterns for this project. For design system rules (error display, layout, dialogs, tokens), use the phoenix-design skill.

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phoenix-llms-txt

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phoenix-pr-screenshot

Screenshot a running Phoenix feature and attach images to a GitHub PR. Builds the frontend, starts Phoenix with env vars, uses agent-browser to capture screenshots, uploads to GCS, and updates the PR body.

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phoenix-release-notes

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phoenix-typescript

TypeScript conventions and patterns for any TypeScript code in the Phoenix monorepo — including js/packages/, app/, and any other TS directories. Use this skill whenever writing, reviewing, or modifying TypeScript code — new functions, types, exports, tests, or refactors. Also trigger when the user asks about TS patterns, naming conventions, or best practices for this project.

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phoenix-cli

Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, review experiments, inspect datasets, and query the GraphQL API. Use when debugging AI/LLM applications, analyzing trace data, working with Phoenix observability, or investigating LLM performance issues.

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phoenix-evals

Build and run evaluators for AI/LLM applications using Phoenix.

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phoenix-tracing

OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.

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