Skills for “agents”

Migrate Python OpenAI Agents SDK applications to Pydantic AI and, when warranted, Pydantic AI Harness. Use for `agents.Agent`, `Runner`, function tools, handoffs, guardrails, sessions, human approval, streaming, or…

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…

Writing documents for agents. Use when creating or editing a skill (its SKILL.md, description or reference files), when modifying AGENTS.md or CLAUDE.md, or when reviewing an agent-facing document that behaves…

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Default guidance for building AI agents. Use for generic requests to build, create, scaffold, design, architect, or implement an AI agent, agent app, tool-calling agent, durable agent, multi-agent system, or scheduled…

…when several units of work might run concurrently through agents - independent investigations, specialist reviews, repository analyses, or plan tasks that look unrelated - covering whether they are genuinely…

Use Snowflake Cortex Agent REST and SQL APIs for listing, describing, creating, updating, deleting, running agents, streaming responses, and SQL wrappers. Use only for direct API workflows; Do not use for MCP-only work.

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,…

…restores, transfers, and manages co-authors for Observal Agents. Use when the user wants to build or install an Agent, change an Agent definition, publish a draft, release a version, or manage Agent…

Use when measuring or improving agent quality and performance — set up evaluators, online monitoring, CI/CD quality gates, observability, or cost optimization. Triggers on: "evaluate my agent", "add evaluator", "measure…

Advanced AI agent benchmark scenarios that push Vercel's cutting-edge platform features — Workflow SDK, AI Gateway, MCP, Chat SDK, Queues, Flags, Sandbox, and multi-agent orchestration. Designed to stress-test skill…

…or Codex itself to Logfire telemetry, or route a coding agent's model requests through Pydantic AI Gateway. Use for coding-session recording, capture policies, Gateway agent configuration, temporary proxy launches,…

Convex is the backend agents get right on the first try: an all-TypeScript reactive platform where the database, server functions, scheduling, file storage, auth, and realtime sync are one type-safe system, every…

Unified entry point for AI-agent work on AWS: evaluate and pick a runtime, generate a full migration plan (for existing workloads), and build an executable POC — all in one flow. Triggers on: which runtime for my agent,…

…issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since…

…runs and a stderr ready-marker contract — designed for AI agents running as…

…connector is connected: it confirms the person can grant agent access, asks whether they want to invite secondary users, then walks them through Manage Your Permissions -> Manage Agents, where they enable the agent…

…from the current session should be recorded for future agents - pitfalls hit, mistakes the user corrected, conventions found, or commands that finally worked, whatever the conversation language - including when the…

Scaffold a new Atomic Agents project from scratch — create the directory, `pyproject.toml`, env file, first agent, and a runnable entry point. Use when the user asks to start a new atomic-agents project from scratch,…

Diagnose and fix a failing or misbehaving Atomic Agents app — import errors, schema validation failures, empty or malformed LLM output, provider role/mode errors, history and context problems, MCP transport errors. Use…