github.com/Arize-ai/phoenix
Skill | Added | Review |
|---|---|---|
phoenix-client-development Guide for the phoenix-client TypeScript package — experiment lifecycle, tracer provider management, and test conventions. | 68 1.23x Agent success vs baseline Impact 100% 1.23xAverage score across 3 eval scenarios Securityby Passed No known issues Reviewed: Version: 924117e | |
phoenix-cli-development Design and implementation guide for the Phoenix CLI (`px`). Covers the noun-verb command structure, dual-audience design (humans and coding agents), Commander.js patterns, configuration resolution, output formats, exit codes, and conventions for adding or modifying commands. Triggers when working on phoenix-cli commands — adding new commands, modifying existing ones, refactoring command structure, or reviewing CLI code. Also triggers on mentions of `px` commands, CLI design, or adding a new resource to the CLI. | 91 2.25x Agent success vs baseline Impact 99% 2.25xAverage score across 3 eval scenarios Securityby Risky Do not use without reviewing Reviewed: Version: 924117e | |
phoenix-rest-api REST API development for Phoenix. Use when adding, modifying, or reviewing endpoints in src/phoenix/server/api/routers/v1/. | 69 Impact — No eval scenarios have been run Securityby Passed No known issues Reviewed: Version: 924117e | |
phoenix-otel-development Guide for the phoenix-otel TypeScript package — OTel registration, stack-based global provider management, and provider lifecycle. | 48 Impact — No eval scenarios have been run Securityby Passed No known issues Reviewed: Version: 924117e | |
mintlify Build and maintain documentation sites with Mintlify. Use when creating docs pages, configuring navigation, adding components, or setting up API references. | 89 1.07x Agent success vs baseline Impact 97% 1.07xAverage score across 3 eval scenarios Securityby Advisory Suggest reviewing before use Reviewed: Version: 924117e | |
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. | 67 Impact — No eval scenarios have been run Securityby Passed No known issues Reviewed: Version: 924117e | |
phoenix-server Backend development guide for the Phoenix AI observability platform (Strawberry GraphQL, SQLAlchemy async, FastAPI). Use this skill when writing or modifying Python server code in the phoenix repo — adding mutations, types, migrations, or tests. Trigger on any backend task touching src/phoenix/server/, src/phoenix/db/, or tests/unit/server/. | 66 Impact — No eval scenarios have been run Securityby Passed No known issues Reviewed: Version: 924117e | |
agent-browser Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools. | 71 4.58x Agent success vs baseline Impact 55% 4.58xAverage score across 3 eval scenarios Securityby Advisory Suggest reviewing before use Reviewed: Version: 924117e | |
phoenix-cli Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, structure trace review with open coding and axial coding, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user is analyzing traces or spans, investigating LLM/agent failures, deciding what to do after instrumenting an app, building failure taxonomies, choosing what evals to write, or asking "what's going wrong", "what kinds of mistakes", or "where do I focus" — even without naming a technique. | 68 Impact — No eval scenarios have been run Securityby Risky Do not use without reviewing Reviewed: Version: 924117e |