by DougTrajano
This package implements Agent Skills (https://agentskills.io) support with progressive disclosure for Pydantic AI. Supports filesystem and programmatic skills.
# Add to your Claude Code skills
git clone https://github.com/DougTrajano/pydantic-ai-skillsGuides for using ai agents skills like pydantic-ai-skills.
Last scanned: 5/30/2026
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"issues": [],
"status": "PASSED",
"scannedAt": "2026-05-30T15:05:23.331Z",
"npmAuditRan": true,
"pipAuditRan": true
}pydantic-ai-skills is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by DougTrajano. This package implements Agent Skills (https://agentskills.io) support with progressive disclosure for Pydantic AI. Supports filesystem and programmatic skills. It has 360 GitHub stars.
Yes. pydantic-ai-skills passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/DougTrajano/pydantic-ai-skills" and add it to your Claude Code skills directory (see the Installation section above).
pydantic-ai-skills is primarily written in Python. It is open-source under DougTrajano on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh pydantic-ai-skills against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Agent Skills for 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.
pydantic-ai-harnessThe harness's own Skills capability is a minimal reader: it injects SKILL.md instructions but
does not enumerate, read, or execute bundled files.
pydantic-ai-skills implements the full package — bundled resources, script execution, remote
registries, programmatic skills, and reload at runtime — so skills that ship a reference document or
a script (including those in Anthropic's skills repository)
run as written. Feature-by-feature comparison:
Why pydantic-ai-skills.
uv add pydantic-ai-skills
Millennials may continue to use pip install pydantic-ai-skills. It still works, like your Spotify
playlist from 2013.
Point a SkillsCapability at one or more skill directories 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(directories=['./skills'])],
)
result = await agent.run('What are the last 3 papers on arXiv about machine learning?')
print(result.output)
SkillsToolset is the same thing as a toolset, for agents built around toolsets=[...]:
from pydantic_ai_skills import SkillsToolset
agent = Agent(model='gateway/openai:gpt-5.2', toolsets=[SkillsToolset(directories=['./skills'])])
Both inject the skill catalog into the agent's instructions automatically and expose four tools:
| Tool | Purpose |
|---|---|
list_skills() |
List available skills (optional — the catalog is already in the prompt) |
load_skill(name) |
Read a skill's full instructions |
read_skill_resource(skill_name, resource_name) |
Read a bundled file such as REFERENCE.md |
run_skill_script(skill_name, script_name, args) |
Run a bundled script with named arguments |
See Quick Start.
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) and description (max 1024 chars) are
required; other frontmatter fields are yours to use. See
Creating Skills.
include / exclude.reload() / auto_reload, exclude_tools, deferred loading, recursive discovery.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.
Contributions are welcome — see Contributing.
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.
MIT License — see LICENSE.