phoenix-skills-audit
Phoenix Skills Audit
Keep the three external-facing skills — phoenix-tracing, phoenix-cli, phoenix-evals —
truthful about what the Phoenix Python clients, TypeScript clients, CLI, and APIs actually
do today. The output is patches applied to the skill files, not a report. The skill
reads recent commits, identifies what changed in user-facing surfaces, and updates the
relevant SKILL.md and references/*.md files in place.
This is a sibling skill to phoenix-docs-gap-audit. The docs-gap-audit produces a report
about gaps in docs/phoenix/; this skill produces edits to .agents/skills/. Skills are
loaded into agent context every time the user asks a question that triggers them, so a
stale skill teaches every future agent the wrong API. That makes drift here strictly
worse than drift in human-facing docs — humans can sanity-check; agents can't.
Targets — the three skills this audit owns
.agents/skills/phoenix-tracing/SKILL.md
.agents/skills/phoenix-tracing/references/*.md
More from arize-ai/phoenix
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.
496phoenix-tracing
OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.
489phoenix-evals
Build and run evaluators for AI/LLM applications using Phoenix.
433agent-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.
65vercel-react-best-practices
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
63phoenix-skill-development
Develop, refine, and maintain skills in the skills/ directory. Use when creating a new skill, updating an existing skill, adding rule files, or improving skill quality and consistency.
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