How to write prose that reads like human technical documentation rather than LLM output. Use whenever writing or editing docstrings, comments, limitations/ docs, READMEs, commit messages or PR descriptions, and when prose reads as smooth, salesy or generic.
Use as the final documentation gate before a capability PR merges. Verifies that a user-facing change keeps the capability README and its unified-docs page in sync with each other and with the code, that every snippet is runnable, and that links follow repo convention. Reports gaps; does not edit.
Bootstrap branch-context on an existing PR. Writes issue-brief.md from the linked issue(s) + current PR state, and backfills pr-decisions.md with decision-bearing entries from already-resolved review threads. Use when picking up a PR mid-flight (yours or someone else's) without prior local context.
Branch-local durable PR state -- issue brief, decisions log, and session handoffs. Read the brief, decisions, and latest handoff at session start; append decisions as you work; write a handoff only on user request or explicit session turnover.
What to do when you open a PR and every time you push -- label the PR, watch CI to green, triage every review comment to a reply and a reaction, and escalate genuine design trade-offs to maintainers. Use whenever you open a PR or push a commit to one.
Extend Pydantic AI agents with batteries-included capabilities from pydantic-ai-harness -- Code Mode (collapse many tool calls into one sandboxed Python execution), a filesystem and shell, sub-agents, planning, context compaction, and more. Use when the user mentions pydantic-ai-harness, CodeMode, Monty, code mode, or…
Build AI agents with Pydantic AI — tools, capabilities (including on-demand loading), structured output, streaming, testing, and multi-agent patterns. Use when the user mentions Pydantic AI, imports pydanticai, or asks to build an AI agent, add tools/capabilities, defer capability loading, stream output, define agents…