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This package implements Agent Skills (https://agentskills.io) support with progressive disclosure for Pydantic AI. Supports filesystem and programmatic skills.
| Date | Stars |
|---|---|
| 2026-07-31 | 351 |
| 2026-08-01 | 353 |
| 2026-08-06 | 353 |
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# pydantic-ai-skills
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
[](https://sonarcloud.io/summary/new_code?id=DougTrajano_pydantic-ai-skills)
[Agent Skills](https://agentskills.io/home) for [Pydantic AI](https://ai.pydantic.dev/).
**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](https://dougtrajano.github.io/pydantic-ai-skills)** — including
[video tutorials](https://dougtrajano.github.io/pydantic-ai-skills/quick-start/#video-tutorials).
## Why This and Not `pydantic-ai-harness`
The harness's own `Skills` capability is a minimal reader: it injects `SKILL.md` instructions but
[does not enumerate, read, or execute bundled files](https://github.com/pydantic/pydantic-ai-harness/tree/main/pydantic_ai_harness/skills).
`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](https://github.com/anthropics/skills))
run as written. Feature-by-feature comparison:
[Why pydantic-ai-skills](https://dougtrajano.github.io/pydantic-ai-skills/comparison/).
## Installation
```bash
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 directories and add it to your agent:
```python
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=[...]`:
```python
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](https://dougtrajano.github.io/pydantic-ai-skills/quick-start/).
## Anatomy of a Skill
```md
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
```
```markdown
---
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 needExcerpt of 6,542 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:a4ad4431ef55d6dc, topic:ai-agents, topic:agent-framework, topic:agentic-ai