Set up, write, and publish documentation sites with Mintlify, and work on existing Mintlify projects. Use when the user wants to create a docs site for a repo or product, turn a docs/ folder or README into a hosted docs site, document an API from an OpenAPI…
Open-source AI observability platform for tracing, evaluating, and improving LLM applications with OpenTelemetry integration
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 js/app/ directory. Triggers on any frontend task — new components, UI…
Run open-source triage on Arize-ai/phoenix issues — classify type, check sufficiency, apply component and complexity labels, flag work that already shipped, investigate complex bugs, tidy formatting, then gate against a contributor policy such as "good…
Create a new Harbor task for evaluating agents. Use when the user wants to scaffold, build, or design a new task, benchmark problem, or eval. Guides through instruction writing, environment setup, verifier design (pytest vs Reward Kit vs custom), and solution…
Manages stacked PRs and splits multi-part work into reviewable branches with gh-stack. Use for stack creation, viewing, edits, push, submit, sync, rebase, merge, or checkout; when asked to split or isolate work for review; whenever a user mentions a stack,…
Write Harbor task verifiers using Reward Kit. Use when creating or editing a task's tests/ directory, adding grading criteria, setting up LLM/agent judges, or designing verifiers that produce a reward score.
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…