Pydantic AI

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Install

pip install "decimalai[pydantic-ai]"

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Use

import decimalai
decimalai.init(api_key="dai_sk_...")

from decimalai.pydantic_ai import install
install(enable_skill_loader=True)

from pydantic_ai import Agent
agent = Agent("openai:gpt-4o", system_prompt="You are helpful")
# Skills are now auto-loaded into every agent.run() call.

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How it works

1. A skills system prompt — a registered system_prompt function that calls SkillRouter.build_prompt_fragment() per turn and prepends the skill menu to your base system prompt.
2. The load_skill tool — registered via tool_plain. Pydantic AI owns its tool loop, so when the model calls load_skill("name"), the full skill body routes back mid-turn. A body served this way counts as delivered and activated on the usage ladder; menu rows alone count as offered.

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Menu mode: full menu, not smart routing

from decimalai.skill_router import SkillRouter

router = SkillRouter(api_key="dai_sk_...")
fragment, routing_id = router.build_prompt_fragment(query=user_message)

agent = Agent("openai:gpt-4o", system_prompt=f"You are helpful.\n{fragment}")

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Tracing

# OpenAI models under Pydantic AI:
decimalai.init(api_key="dai_sk_...", openai=True)     # raw OpenAI SDK tracing

# Anthropic models:
decimalai.init(api_key="dai_sk_...", anthropic=True)

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Caveats

• install() only affects Agents constructed after it runs — call it before you build your agents.
• This adapter never reads or writes disk skills (no disk_sync parameter). If you run inside a disk-loading runtime (Claude Code, Cursor), the SDK logs a one-shot warning about duplicate-injection risk when the loader is enabled.
• Skill-loader failures are non-fatal by design: if the router is unreachable, the system prompt gains no skills and load_skill returns an error string the model can read — your agent keeps running.

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What’s next