pydantic-ai-skills

Remote skill registries and bundled-file execution for Agent Skills in Pydantic AI.

Agent Skills are modular packages of instructions, resources, and scripts that teach an agent to handle a specialized task. On disk, a skill is just a folder: a SKILL.md file holding a name, a description, and Markdown instructions, plus any reference documents and executable scripts the task needs.

Your agent starts out seeing only the name and description of each skill. When a task calls for one, it loads that skill's full instructions, and reads a reference document or runs a script only if it actually needs to. This is progressive disclosure: your skill library can grow without every skill paying for space in the prompt.

📖 Full documentation — including video tutorials.

How This Relates to pydantic-ai-harness

pydantic-ai-harness ships a Skills capability that reads SKILL.md packages from local directories and turns each into a deferred Pydantic AI capability. It stops there by design — it does not enumerate, read, or execute bundled files, and it has no notion of a remote source.

pydantic-ai-skills is the companion that fills those gaps. It requires harness and delegates to it, so SKILL.md parsing, validation, the catalog and instruction rendering are all upstream's, and adds:

• Remote registries — Git and S3 sources, with composition (filter, prefix, rename, merge).
• Bundled files — read_skill_resource and run_skill_script, so a skill that ships a reference document or a script (including those in Anthropic's skills repository) runs as written.
• Sandboxed execution — keep untrusted scripts off the host.
• ${SKILL_DIR} resolution — harness leaves the placeholder in place; this substitutes the path.
• Programmatic skills — skills defined in Python, in the same catalog.

If your skills are instructions and nothing else, use harness directly — it is a smaller dependency and identical behaviour. Feature-by-feature: comparison.

Upgrading from v1? v2 is a clean break: SkillsToolset, SkillsDirectory, reload() and the list_skills / load_skill tools are gone, replaced by harness and Pydantic AI's own load_capability. See the migration guide.

Installation

uv add pydantic-ai-skills

Millennials may continue to use pip install pydantic-ai-skills. It still works, like your Spotify playlist from 2013.

Quick Start

Point a SkillsCapability at one or more skill libraries and add it to your agent:

from pydantic_ai import Agent
from pydantic_ai_skills import SkillsCapability

agent = Agent(
    model='gateway/openai:gpt-5.2',
    instructions='You are a helpful research assistant.',
    capabilities=[SkillsCapability('./skills')],
)

result = await agent.run('What are the last 3 papers on arXiv about machine learning?')
print(result.output)

Or pull them from a repository:

from pydantic_ai_skills import GitSkillsRegistry, SkillsCapability

capability = SkillsCapability(
    './skills',
    registries=[GitSkillsRegistry('https://github.com/anthropics/skills', path='skills')],
)

Each skill becomes its own deferred capability: the model sees names and descriptions up front, loads the ones it needs with Pydantic AI's built-in load_capability, then reaches that skill's files with the two tools this package adds:

Both stay behind the same boundary as the skill's instructions: by default they refuse a skill the model has not loaded.

See Quick Start.

Anatomy of a Skill

my-skill/
├── SKILL.md      # Required: YAML frontmatter + Markdown instructions
├── REFERENCE.md  # Optional: extra docs, read on demand
├── scripts/      # Optional: executable scripts
└── resources/    # Optional: templates, data files

---
name: my-skill
description: Brief description of what this skill does and when to use it
---

# My Skill

## When to Use This Skill

Use this skill when you need to...

## Instructions

1. Step 1
2. Step 2

name (max 64 chars, lowercase letters, numbers and hyphens; it must match the directory) and description (max 1024 chars) are the fields the runtime acts on. Other frontmatter is accepted but inert — including behavioural fields such as allowed-tools, which do not restrict anything here. See Creating Skills.

Beyond the Filesystem

• Programmatic skills — define skills in Python with decorators or dataclasses.
• Registries — load skills from Git repositories, S3, or custom sources, and compose them (combine, filter, prefix, rename).
• Skill selection — give each agent a subset of a shared library with include / exclude.
• Sandboxing — run a skill's scripts in a container or virtual filesystem instead of on the host.
• Advanced features — custom script executors, ${SKILL_DIR} resolution, and rebuild strategies.

Security

Only use skills from sources you trust. Skills give agents new capabilities through instructions and code, so a malicious skill can direct an agent to invoke tools or execute code in ways that don't match its stated purpose — with risks including data exfiltration and unauthorized system access. Audit any skill from an unknown source before use. See Security & Deployment.

Related Resources

• Agent Skills Specification
• Anthropic Agent Skills docs and best practices
• Agent Skills Cookbook
• Pydantic AI Documentation

Contributing

Contributions are welcome — see Contributing.

Acknowledgments

Thanks to Anthropic for the Agent Skills open format, the Pydantic AI team for the framework, and the community for feedback and contributions.

This project was highly inspired by pydantic-deepagents, which provided foundational ideas and patterns for agent skills and progressive disclosure in Pydantic AI.

License

MIT License — see LICENSE.