---
id: skills-ref
version: "0.1.1"
license: Apache-2.0
license_treatment: permissive
maintenance: aging
---

# skills-ref — Reference library for Agent Skills

License: permissive · Maintenance: aging · Downloads: 230.0K/mo

## What it is and what it does

skills-ref is a reference library for working with Agent Skills, an open format for packaging AI agent capabilities. It provides validation, metadata extraction, and XML prompt generation for skill directories—folders containing instructions, scripts, and resources that agents can discover and use. The library is maintained by Anthropic as part of an open-source initiative.

You use it to validate that skill directories conform to the format, read skill metadata from SKILL.md frontmatter, and generate XML blocks suitable for inclusion in agent system prompts. It includes both a Python API and CLI tools (agentskills validate, agentskills read-properties, agentskills to-prompt) for skill management workflows. The package depends on click for CLI scaffolding and strictyaml for safe YAML parsing.

Use it for:

- Validate skill directories before publishing or distributing them to ensure they meet the Agent Skills specification.
- Extract skill metadata and properties programmatically to build skill catalogs or discovery systems.
- Generate XML prompt blocks from multiple skills to inject into agent system prompts at runtime.
- Automate skill format checking in CI/CD pipelines for skill repositories.
- Build tooling around the Agent Skills format for skill authoring or management platforms.

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Validates, parses, and generates prompt-compatible XML from Agent Skills—a standardized format for packaging AI agent capabilities as reusable skill modules.

Yes, if you are actively building or managing skills in the Agent Skills format or integrating them into agent systems. The low install friction and permissive license make it a safe dependency. However, the Alpha status and aging maintenance signal mean the format and library are still evolving; verify that Agent Skills adoption aligns with your agent framework before committing to the format.

## Install

pip install skills-ref
uv add skills-ref
poetry add skills-ref

## Installing skills-ref

Before you install: Low friction: pure Python wheel with just click and strictyaml as runtime dependencies. Marked as Alpha and aging (216 days since release with no recent commits tracked), so treat as early-stage tooling.

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.

Quickstart:

pip install skills-ref

from pathlib import Path
from skills_ref import validate, read_properties, to_prompt

errors = validate(Path("my-skill"))
props = read_properties(Path("my-skill"))
prompt = to_prompt([Path("skill-a"), Path("skill-b")])

Requires Python 3.11 or later.

Verify before relying:

- Whether the skill format is actively maintained or standardized across the AI agent ecosystem.
- Real-world adoption rate and whether skills published by the community are discoverable or indexed.
- Whether validation catches all common skill authoring mistakes or only structural issues.

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: aging
- Downloads: 230.0K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

agent skills validation, llm skill format parser, ai agent capability packaging, skill metadata extraction, agent prompt generation, skill directory validator, ai capability management, agent-skills, llm-tooling, prompt-engineering

[View on SkillFed](https://skillfed.io/packages/skills-ref) · [View on PyPI](https://pypi.org/project/skills-ref/)