10 actions in 9 pieces of software · ranked by words, meaning and measured trust · 636 ms

1. 1phoenix-tracingverified and signedpassport

   skillgithub/awesome-copilotrecord

   • phoenix-tracing

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

2. 2phoenix-observabilityverified and signedpassport

   skillorchestra-research/ai-research-skillsrecord

   • phoenix-observability

     Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

3. 3phoenix-cliverified and signedpassport

   skillgithub/awesome-copilotrecord

   • 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 f

4. 4phoenix-cliverified and signedpassport

   skillarize-ai/phoenixrecord

   • phoenix-cli

     Debug LLM applications using the Phoenix CLI (`px`, from @arizeai/phoenix-cli). Fetch traces, spans, and sessions, annotate them, analyze errors, measure how often a failure or pattern occurs across traces, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use

5. 5phoenix-evalsverified and signedpassport

   skillarize-ai/phoenixrecord

   • phoenix-evals

     Build, run, and validate evaluators for AI/LLM applications with Phoenix, in Python or TypeScript (including Vercel AI SDK apps) — code-based checks and LLM-as-a-judge, run over exported traces or dataframes or as Phoenix experiments, gate them in CI, and validate judges against human-labeled data.

6. 6phoenix-evalsverified and signedpassport

   skillgithub/awesome-copilotrecord

   • phoenix-evals

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

7. 7@arizeai/phoenix-mcpfound in code, not yet checkedno passport yet
   • list-traces

   • get-trace

8. 8braintrust-tracingverified and signedpassport

   skillparcadei/continuous-claude-v3record

   • braintrust-tracing

     Braintrust tracing for Claude Code - hook architecture, sub-agent correlation, debugging

9. 9phoenix-mcp-evalfound in code, not yet checkedno passport yet
   • query_traces

     Run a structured query over trace data by time range or metadata filter.