skills-ref
Reference library for Agent Skills
Decision gist · record as of 2026-08-14
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.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later.
- 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 · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.
last release 2026-01-10 (216 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 229,963 downloads/mo, #9,118 on PyPI
Alternatives
Verify before relying
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")])- 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.
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 on this page. Verify before relying on it.
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
skills-ref on PyPI
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.
Requires Python 3.11 or later.
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")])
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 the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesclickstrictyaml |
| Maintenance | Aging 216 days since the last release |
| First released | |
| Downloads | 229,963 / month, #9,118 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Topic :: Software Development :: Libraries :: Python Modules |
Evidence: skills_ref-0.1.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “agent skills validation”
- skills-refValidates, parses, and generates prompt-compatible XML from Agent…
- skillsawA linter for AI agent instruction files that detects structural…
- pydantic-ai-skillsTeaches agents to handle specialized tasks through modular skill…
Give your agent the search over MCP, or paste the wish link into any chat.
More Python Modules packages
Converts domain names between Unicode and ASCII-compatible encoding (Punycode) according to IDNA 2008 and Unicode Technical Standard 46, with security validation and broader script coverage than the standard library.
Install it if you work with internationalized domain names, need to validate domains, or use HTTP clients that depend on it transitively.
Setuptools is a Python build backend and package management tool that handles building, distributing, and installing Python packages, including support for C/C++ extension modules.
PyYAML parses and emits YAML 1.1 data format, enabling serialization and deserialization of configuration files and Python objects to and from human-readable YAML text.
Pydantic validates Python data structures against type hints, coercing and checking input at runtime to ensure it matches a declared schema.
Provides reusable metadata objects for use with PEP-593 `typing.Annotated` to express common constraints like bounds, collection sizes, and predicates on types.
Install it if you use or build libraries that need to express type constraints in a standardized, inspectable way—or if you want to annotate your own types with…
Provides runtime tools to inspect and introspect Python type annotations, enabling programmatic examination of type hints at execution time.
See also pydantic-ai-skills · skillsaw · cisco-ai-skill-scanner · boost-skill-cli · doclang · google-agents-cli · memsearch · apm-cli · deepagents · openhands-tools