Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), workspaces, structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydantic_ai, or asks to build an AI agent, add…
Extend Pydantic AI agents with capabilities from pydantic-ai-harness -- the Coder coding agent, file and shell tools in local or sandboxed workspaces (Modal, E2B, Sprites, Daytona, boxd, smolvm, BoxLite), Code Mode, sub-agents and planning, memory and skills,…
Migrate Python LangChain, LangGraph, or Deep Agents applications to Pydantic AI and, when the source uses harness features, Pydantic AI Harness. Use for LangChain agents, chains, LCEL, direct LangGraph graphs, persistence, interrupts, streaming, and…
Migrate Python LangChain Deep Agents applications to Pydantic AI and Pydantic AI Harness. Use when the source uses the upstream `deepagents` package or demonstrably reproduces its middleware, backends, skills, memory, subagents, or sandbox contracts. Use…
Evaluate and complete an issue or PR where the submitted patch fixes only a narrow symptom of the reported pain point. Use when a contribution may miss adjacent integration surfaces, provider/spec semantics, roundtrip behavior, tests, docs, or historical…
Study a problem or GitHub issue in a fresh worktree, plan a fix, optionally implement it, and open the initial PR. Use when starting work on a new problem — not for advancing existing PRs.
Review candidate content locally under the scope, exemptions, and three-review budget defined by pushing-commits-to-the-repo
Capture a real, net-positive bug or improvement you discovered that is OUT OF SCOPE for the current PR — the PR already closes its issue and is stable, and the new work is non-trivial (adds its own decisions, carries uncertainty, or widens blast radius beyond…