agent

name	Agent
description	Use when creating, validating, or integrating reusable skill packages for AI agents. Reach for this skill when building domain-specific instructions, packaging workflows, or setting up skill discovery in agent systems.
metadata	{"mintlify-proj":"agent","version":"1.0"}

Agent Skills

Product summary

Agent Skills is a lightweight, open format for extending AI agent capabilities with specialized knowledge and workflows. Skills are directories containing a SKILL.md file (YAML frontmatter + Markdown instructions) plus optional supporting files (scripts, references, assets). Use the skills-ref CLI to validate skills and generate prompt XML for agent integration. Primary documentation: https://agentskills.io

When to use

Reach for this skill when:

• Creating a new skill: You need to package domain expertise, repeatable workflows, or new agent capabilities into a reusable format
• Validating skills: You're checking that a skill's SKILL.md file meets format requirements before deployment
• Integrating skills into agents: You're setting up skill discovery, loading metadata, or injecting skills into agent system prompts
• Authoring instructions: You're writing the Markdown body of a skill to guide agent behavior
• Managing skill resources: You're organizing scripts, templates, reference files, or assets alongside skill instructions

Quick reference

SKILL.md frontmatter (required fields)

Field	Constraints	Example
name	Max 64 chars, lowercase + hyphens only, no leading/trailing hyphens	pdf-processing
description	Max 1024 chars, non-empty, describes what skill does and when to use	Extract text and tables from PDFs, fill forms, merge documents.

SKILL.md optional frontmatter fields

Field	Purpose	Example
license	License name or reference to bundled license file	MIT or licenses/LICENSE.txt
compatibility	Environment requirements (max 500 chars)	Requires Python 3.8+, pdfplumber library
metadata	Arbitrary key-value pairs for custom properties	author: org-name version: "1.0"
allowed-tools	Space-delimited pre-approved tools (experimental)	Bash(git:*) Bash(jq:*)

Directory structure

skill-name/
├── SKILL.md              # Required: frontmatter + instructions
├── scripts/              # Optional: executable code
├── references/           # Optional: detailed reference material
└── assets/               # Optional: templates, images, data files

skills-ref CLI commands

# Validate a skill directory
skills-ref validate ./my-skill

# Generate <available_skills> XML for agent prompts
skills-ref to-prompt /path/to/skill1 /path/to/skill2

File references in SKILL.md

Use relative paths from skill root:

See [the guide](references/REFERENCE.md) for details.
Run the script: `scripts/extract.py`

Decision guidance

When to use filesystem-based vs tool-based agent integration

Approach	When to use	Activation	Resource access
Filesystem-based	Agent has shell/bash environment; maximum capability needed	Agent issues cat /path/to/skill/SKILL.md	Shell commands access bundled files
Tool-based	Agent lacks dedicated computer environment; sandboxed execution	Developer implements custom tools	Tools provide access to bundled assets

When to include optional frontmatter fields

Field	Include when	Skip if
license	Skill uses third-party code or has specific licensing	Skill is internal-only or unlicensed
compatibility	Skill requires specific system packages, Python versions, or network access	Skill is pure Markdown instructions
metadata	Tracking author, version, or custom properties is important	Not needed for simple skills
allowed-tools	Restricting which tools the skill can invoke is required	Agent doesn't support tool restrictions

When to move content to separate files

Content type	Keep in SKILL.md	Move to separate file
Core instructions	< 500 lines	Detailed reference material
Quick examples	Yes	Exhaustive API documentation
Decision trees	Yes	Large lookup tables or schemas
Step-by-step workflows	Yes	Multi-page tutorials

Workflow

Creating a new skill

1. Create the directory structure: Make a folder named skill-name (lowercase, hyphens only)

2. Write the SKILL.md file:

   • Start with YAML frontmatter: name and description (required)
   • Write the Markdown body with clear instructions
   • Keep the main file under 500 lines
   • Use relative paths for file references: scripts/extract.py, references/GUIDE.md

3. Organize supporting files:

   • scripts/: Executable code (Python, Bash, etc.)
   • references/: Detailed documentation, lookup tables, schemas
   • assets/: Templates, images, data files

4. Validate the skill:

   skills-ref validate ./skill-name
   

   Fix any frontmatter errors (name format, description length, etc.)

5. Test the skill: Read the SKILL.md file to verify instructions are clear and complete

Integrating skills into an agent

1. Discover skills: Scan configured directories for folders containing SKILL.md files

2. Load metadata at startup: Parse only the YAML frontmatter from each skill:

   name: pdf-processing
   description: Extract text and tables from PDFs...
   

   This keeps initial context usage low (~100 tokens per skill)

3. Generate prompt XML:

   skills-ref to-prompt /path/to/skills/*
   

   Output includes name, description, and location for each skill

4. Inject into system prompt: Add the XML to your agent's system prompt so it knows available skills:

   <available_skills>
     <skill>
       <name>pdf-processing</name>
       <description>Extract text and tables from PDFs...</description>
       <location>/path/to/skills/pdf-processing/SKILL.md</location>
     </skill>
   </available_skills>
   

5. Activate on demand: When a user task matches a skill's description, load the full SKILL.md into context (~5000 tokens max)

6. Execute resources: Load referenced files or run scripts only when the skill instructions require them

Common gotchas

• Name format violations: Names must be lowercase with hyphens only, no leading/trailing hyphens. my-skill ✓, MySkill ✗, -my-skill ✗
• Description too long: Max 1024 characters. Descriptions longer than this will fail validation. Be concise about what the skill does and when to use it.
• Forgetting YAML delimiters: Frontmatter must start and end with --- on its own line. Missing delimiters break parsing.
• Absolute paths in file references: Always use relative paths from skill root (scripts/extract.py), never absolute paths (/home/user/scripts/extract.py)
• Bloated SKILL.md: Keeping the main file under 500 lines is a guideline, not a hard limit, but large files waste context. Move detailed reference material to references/ subdirectory.
• Missing location field for filesystem agents: When injecting skills into filesystem-based agent prompts, include the absolute path to SKILL.md. Tool-based agents can omit this.
• Not validating before deployment: Always run skills-ref validate before sharing or deploying a skill. Frontmatter errors are silent until validation.
• Unclear "when to use" description: The description field is critical for agent matching. Write it as a clear trigger: "Use when the user needs to extract text from PDFs" not "PDF processing skill".

Verification checklist

Before submitting a skill:

• SKILL.md frontmatter has name (max 64 chars, lowercase + hyphens) and description (max 1024 chars)
• Frontmatter is wrapped in --- delimiters on separate lines
• All file references use relative paths from skill root (e.g., scripts/extract.py)
• Main SKILL.md is under 500 lines; detailed material moved to references/ or assets/
• Skill passes validation: skills-ref validate ./skill-name
• Instructions are clear and actionable (imperative voice, step-by-step)
• Optional fields (license, compatibility, metadata) are accurate if included
• Skill description clearly states when an agent should use it (not just what it does)

Resources

• Comprehensive navigation: https://agentskills.io/llms.txt
• Full specification: https://agentskills.io/specification
• Integration guide: https://agentskills.io/integrate-skills
• Example skills: GitHub repository (linked from agentskills.io)

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For additional documentation and navigation, see: https://agentskills.io/llms.txt