migrating-claude-agent-sdk-to-pydantic-ai

migrating-claude-agent-sdk-to-pydantic-ai is a skill for Codex from pydantic/pydantic-ai. It costs 90 tokens per session (1,275 once invoked), scanned A, original, MIT.

A migration guide for moving Python applications from the Claude Agent SDK, the software behind Claude Code’s agent loop, to Pydantic AI. It follows a real request through tools, sessions, permissions, events, persistence, and side effects before choosing replacements.

In plain words
What is it for?
Use it when an application uses the Claude Agent SDK’s queries, clients, built-in tools, hooks, permissions, skills, sessions, or subagents and needs a Pydantic AI migration.
Why use it?
It helps preserve the behavior an application exposes instead of copying Claude Code’s process or API shape. It also separates conversation history, workflow checkpoints, long-term memory, and workspace state.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions subagents; mentions Claude Code; installed under .agents/ (shared by several agents).

Good fit Use it when an application uses the Claude Agent SDK’s queries, clients, built-in tools, hooks, permissions, skills, sessions, or subagents and needs a Pydantic AI migration.

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Install with agentmods
npx agentmods add skills/pydantic/pydantic-ai/migrating-claude-agent-sdk-to-pydantic-ai
About the project

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.

pydantic/pydantic-ai · 20,645 stars · on GitHub · pydantic.dev

Install

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.

Any agent
npx skills add pydantic/pydantic-ai --skill migrating-claude-agent-sdk-to-pydantic-ai
Clone the repo
git clone --depth 1 https://github.com/pydantic/pydantic-ai

Made for: Codex.

Wrote 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.

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README.md
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Your own site
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<a href="https://agentmods.dev/skills/pydantic/pydantic-ai/migrating-claude-agent-sdk-to-pydantic-ai"><img src="https://agentmods.dev/badge/skills/pydantic/pydantic-ai/migrating-claude-agent-sdk-to-pydantic-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 90 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,275 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00090 $0.01275
Opus 5.5 $0.00036 $0.00510
Sonnet 5.5 $0.00018 $0.00255
Haiku 4.5 $0.00009 $0.00128

Measured 1mo ago against content hash 72f0b0308584, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

migrating-claude-agent-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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

pydantic_ai_slim/pydantic_ai/.agents/skills/migrating-claude-agent-sdk-to-pydantic-ai/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Migrate Claude Agent SDK to Pydantic AI

Preserve observable behavior, not the Claude Code process or API shape. Migrate the smallest complete caller path and keep application infrastructure in place.

Trace the source before choosing a target

  1. Read repository instructions, dependencies, tests, and the runtime entrypoint. Record the installed Claude Agent SDK, bundled Claude Code CLI, Pydantic AI, and Harness versions.
  2. Trace one real request from query() or ClaudeSDKClient through prompts, tools, events, results, state, persistence, approvals, and side effects that callers use. Establish a focused baseline or characterization test.
  3. Separate these source contracts when present:
    • fresh query() calls, live ClaudeSDKClient continuation, disk/external-store resume, transcript forks, and file rewind;
    • tool availability, automatic approval, policy callbacks, and OS/container isolation;
    • completed messages, raw token deltas, lifecycle events, and terminal results;
    • conversation history, workflow checkpoints, model-owned plans, long-term memory, and workspace state;
    • model-directed subagents from application-owned loops, queues, retries, and schedulers.
  4. Record each observed contract, its owner, semantic difference, and executable proof. An unobserved Claude Code feature is not migration scope.

Read Research and concept mapping for the detected source features. Read Verification and cutover before implementation.

Choose the smallest target

  • Core: use pydantic_ai.Agent for model calls, the agent loop, typed dependencies, tools, outputs, normalized messages, generic hooks, streaming, MCP, approvals, usage limits, instrumentation, and durable-runtime integrations.
  • Harness: add pydantic-ai-harness only for observed reusable policy such as coding filesystem/shell tools, repository context, planning, memory, model-directed subagents, model-agnostic context management, or Agent Skills. Harness capabilities compose through the core agent loop; Harness is not a second runtime.
  • Application: retain authentication, service clients, databases, queues, schedulers, deployment, product state, session lookup, tenant policy, and existing transports unless the requested slice includes them.
  • Gap: name behavior that no supported public seam preserves, explain its impact, and test a bounded adapter. Do not create a lookalike ClaudeSDKClient or emulate Claude transcript files merely to hide a difference.

Read the full file on GitHub · 58 lines

Files

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.

Changes

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.

  1. 1mo ago First seen · 58 lines · 90 tokens per session scan A 72f0b0308584

Subscribe to this mod's changes

migrating-claude-agent-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 90 tokens to every session and 1,275 once invoked, about $0.0004 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.