Pydantic AI is a typed Python SDK for building AI agents that can use different language models and interfaces, including voice, image generation, and embeddings. Developers use it for applications ranging from structured data extraction to long-running multi-agent work. The catalogue entries provide workflows and configuration for its coding-agent and harness features.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add pydantic/pydantic-ai --skill migrating-openai-agents-sdk-to-pydantic-aigit clone --depth 1 https://github.com/pydantic/pydantic-aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pydantic/pydantic-ai/migrating-openai-agents-sdk-to-pydantic-ai)<a href="https://agentmods.dev/skills/pydantic/pydantic-ai/migrating-openai-agents-sdk-to-pydantic-ai"><img src="https://agentmods.dev/badge/skills/pydantic/pydantic-ai/migrating-openai-agents-sdk-to-pydantic-ai/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pydantic/pydantic-ai/migrating-openai-agents-sdk-to-pydantic-ai"><img src="https://agentmods.dev/badge/skills/pydantic/pydantic-ai/migrating-openai-agents-sdk-to-pydantic-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00087 | $0.01406 |
| Opus 5.5 | $0.00035 | $0.00562 |
| Sonnet 5.5 | $0.00017 | $0.00281 |
| Haiku 4.5 | $0.00009 | $0.00141 |
Grade A, and why
migrating-openai-agents-sdk-to-pydantic-ai scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- migrating-openai-agents-sdk-to-pydantic-ai — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Migrate OpenAI Agents SDK to Pydantic AI
Preserve caller-visible behavior, not OpenAI Agents SDK object shapes. Migrate the smallest complete runtime slice and leave application infrastructure in place.
Work from the running application
- Read repository instructions, dependency files, tests, and runtime entrypoints. Record the installed
openai-agents, Pydantic AI, and Harness versions. - Trace one representative
Runner.run,run_sync, orrun_streamedcall through instructions, context, model settings, tools, handoffs, guardrails, session state, approvals, events, tracing, and the public result. Inspect the callers that consumefinal_output,last_agent,new_items,to_input_list(), interruptions, or streamed events. - Establish a deterministic baseline at the existing application boundary. Record only behavior the active path uses.
- Classify the slice before designing it:
- Ordinary agent: use one reusable Pydantic AI
Agentwith typed dependencies, tools, and outputs. - Manager with specialists: use explicit application orchestration, an agent tool, or Harness
SubAgentsaccording to who must own the final response. - Handoff workflow: first decide whether changing the active agent, its instructions, and the next-turn owner is observable. A nested agent tool is not a handoff.
- Sandbox or coding agent: evaluate Harness
Coderand its component capabilities. Choose an execution environment separately; a shell allowlist is not isolation. - Realtime or voice path: treat transport, interruption, audio, and live-session behavior as a separate migration slice using Pydantic AI realtime agents.
- Product runtime: retain authentication, storage, queues, deployment, and service integrations unless explicitly placed in scope.
- Ordinary agent: use one reusable Pydantic AI
- Add or preserve characterization tests, migrate one vertical slice behind the existing public boundary, and run the original plus focused parity tests.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 49 lines · 87 tokens per session scan A a4d08cccc6f6
migrating-openai-agents-sdk-to-pydantic-ai is a skill published in the GitHub repository pydantic/pydantic-ai (20,645 stars, last pushed today), licensed MIT. It adds 87 tokens to every session and 1,406 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-16.
Other skills, from other repositories
test-generator
Generate pytest test cases for Python functions and classes.
python-expert
Python expert for stdlib, packaging, type hints, async/await, and performance optimization.
pydantic-ai-agents
Build and debug Pydantic AI v2 agents using best practices for dependencies, instructions, tools, capabilities, hooks, and structured output validation. Use when the user wants to: (1) Create a new Pydantic AI agent, (2) Debug or fix an existing agent, (3) Add features like tools, validators, capabilities, hooks, or…
django-patterns
Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps.
accelerate
Run PyTorch training across GPUs with minimal changes.
pytorch-patterns
PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.