Agent skill

Agent Skills

by magnus919 in magnus919/agent-skills

A skill your agent uses when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client.

MITAuto-check passedAI & LLM Engineering

Install Agent Skills

skills CLI
$ npx skills add magnus919/agent-skills --skill agent-skills -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install magnus919/agent-skills agent-skills --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/magnus919/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent-skills .claude/skills/agent-skills && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agent-skills
GitHub stars
115
Token cost
~3k tokens
SKILL.md length
1,455 words
Files
12 (incl. references)
Skills in repo
131
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client.

  • Works in 7 steps: Read the specification before changing… → Ground instructions in real domain… → Keep the skill a coherent, triggerable… → …
  • Editing Agent Skills-format skills
  • SKILL.md covers Directory Structure, Required Workflow, SKILL.md Format and Progressive Disclosure, plus 6 more sections
  • Calls ruby

What it does

Agent Skills is an agent skill from magnus919/agent-skills. Use this skill when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client. It covers directory structure, SKILL.md metadata, progressive disclosure, evals, and repository conventions. Do not use this skill for general software work that does not involve the Agent Skills format or lifecycle.

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including reference files (for example `README.md`, `evals/evals.json` and `references/best-practices.md`).

It sits in AI & LLM Engineering, covering LLM evaluation and Skill management. The repository describes itself as: Curated collection of AI agent skills for Hermes and other agent frameworks. The licence is MIT.

When your agent uses it

  • Editing Agent Skills-format skills
  • Implementing skill discovery and loading in an agent client
  • General software work that does not involve the Agent Skills format

Example prompts

  • “/agent-skills”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Read the specification before changing SKILL.md metadata or directory structure.
  2. Ground instructions in real domain knowledge, project artifacts, and observed failure modes. Read best practices when designing or…
  3. Keep the skill a coherent, triggerable unit. Put only essential instructions in SKILL.md; put conditional detail in focused reference…
  4. Use a precise description that says what the skill does, when it applies, and when it does not apply. For skills with meaningful overlap…
  5. For every new skill, create evals/evals.json with at least five representative output-quality cases. Each case needs a realistic prompt…
  6. When bundling executable code, read using scripts. Document prerequisites and non-interactive invocation in the skill.
  7. Before handoff, run the validation checks in this skill and correct every finding.

What it can do on your machine

Read from SKILL.md and the folder at commit 22b4723. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • ruby

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • agentskills.io
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agent Skills loads about 3k tokens when it runs, and up to ~34k if it reads all its reference files. Until then it costs about 95 tokens; SKILL.md has 1,455 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~95
When it runs · the whole SKILL.md, loaded when a task matches
~3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~34k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from magnus919/agent-skills at commit 22b4723, republished under its MIT licence (© magnus919). 1,455 words, ~3,024 tokens.

Download SKILL.mdSave it as .claude/skills/agent-skills/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
agent-skills
description
Use this skill when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client. It covers directory structure, SKILL.md metadata, progressive disclosure, evals, and repository conventions. Do not use this skill for general software work that does not involve the Agent Skills format or lifecycle.
license
MIT

Agent Skills Standard Reference

This skill documents the Agent Skills open format — a standardized way to give AI agents new capabilities and expertise. Follow this workflow when creating or editing skills in this repository.

Authoritative source: agentskills.io/specification. The bundled specification is a working snapshot; check the authoritative source when currentness matters.


Directory Structure

A skill is a directory containing, at minimum, a SKILL.md file:

skill-name/
├── SKILL.md          # Required: metadata + instructions
├── evals/            # Required for new skills in this repository
├── scripts/          # Optional: executable code
├── references/       # Optional: documentation
├── assets/           # Optional: templates, resources
└── ...               # Any additional files or directories

Required Workflow

Create or edit a skill
  1. Read the specification before changing SKILL.md metadata or directory structure.
  2. Ground instructions in real domain knowledge, project artifacts, and observed failure modes. Read best practices when designing or materially revising instructions.
  3. Keep the skill a coherent, triggerable unit. Put only essential instructions in SKILL.md; put conditional detail in focused reference files and state exactly when to read each one.
  4. Use a precise description that says what the skill does, when it applies, and when it does not apply. For skills with meaningful overlap, name the nearest alternative or prerequisite in a ## When not to use section. Test the boundary with at least three should-trigger prompts and two should-not-trigger near-misses; keep these harness-specific trigger checks separate from portable output-quality evals. Read optimizing descriptions for trigger design.
  5. For every new skill, create evals/evals.json with at least five representative output-quality cases. Each case needs a realistic prompt, an expected outcome, and observable assertions. Include edge cases that exercise risky or ambiguous behavior. Read evaluating skills for the eval format and iteration workflow.
  6. When bundling executable code, read using scripts. Document prerequisites and non-interactive invocation in the skill.
  7. Before handoff, run the validation checks in this skill and correct every finding.
Review a skill
  1. Validate the required frontmatter, field constraints, parent-directory/name match, and YAML syntax against the specification.
  2. Check that the description has both positive and negative trigger boundaries, the workflow is actionable, and resource references are conditional and reachable.
  3. Check that any script has documented dependencies, safe non-interactive inputs, clear errors, and structured output where useful.
  4. For this repository, also verify its required human-facing README.md: title, Why Install This Skill, What You Get, Quick Start (unless genuinely reference-only), Triggers, and Requirements. Keep it human-facing, concise, and free of agent-only instructions.
  5. Verify every new skill has evals/evals.json with at least five output-quality cases, and check that their expected outcomes and assertions test meaningful behavior. For an existing skill without evals, flag the gap but do not block the review solely for that legacy absence. Read evaluating skills before declaring the work complete.
Client implementation work

When implementing skill discovery, activation, or context management in an agent product, read client implementation guidance. Do not apply client conventions such as search paths as universal format requirements.

SKILL.md Format

The SKILL.md file must contain YAML frontmatter followed by Markdown body content.

Frontmatter Fields
FieldRequiredConstraints
nameYesMax 64 chars. Lowercase letters, numbers, and hyphens only. Must not start or end with a hyphen. Must match the parent directory name.
descriptionYesMax 1024 chars. Non-empty. Describes what the skill does and when to use it.
licenseNoLicense name or reference to a bundled license file.
compatibilityNoMax 500 chars. Indicates environment requirements.
metadataNoArbitrary key-value mapping.
allowed-toolsNoSpace-separated string of pre-approved tools. (Experimental)
name field rules
  • 1–64 characters
  • Only lowercase unicode alphanumeric (a-z, 0-9) and hyphens (-)
  • Must not start or end with a hyphen
  • Must not contain consecutive hyphens (--)
  • Must match the parent directory name
description field rules
  • 1–1024 characters
  • Should describe both what the skill does and when to use it
  • Should include specific keywords that help agents identify relevant tasks
compatibility field rules
  • If present, it must be 1–500 characters
  • Include it only for concrete environment requirements, such as a required product, system package, network access, or runtime
metadata field rules
  • Must be a map of string keys to string values
  • Use reasonably unique keys to avoid collisions with other clients or tools
Body Content

The Markdown body has no format restrictions beyond being helpful to the agent. Recommended sections:

  • Step-by-step instructions — the procedure the agent should follow
  • Examples of inputs and outputs — what data looks like going in and coming out
  • Common edge cases — situations the agent might not handle correctly without guidance
  • Gotchas — environment-specific facts that defy reasonable assumptions

Keep SKILL.md under 500 lines and 5000 tokens. Move detailed reference material to separate files in references/.

Progressive Disclosure

Agents load skills in three stages:

  1. Metadata (~100 tokens): name and description loaded at startup for all skills
  2. Instructions (< 5000 tokens recommended): Full SKILL.md loaded when activated
  3. Resources (as needed): Files in scripts/, references/, assets/ loaded on demand

Supporting Directories

scripts/

Executable code agents can run. Scripts should:

  • Be self-contained or clearly document dependencies
  • Include helpful error messages
  • Handle edge cases gracefully
  • Use relative paths from the skill root (e.g., scripts/extract.py)
  • Be explicit about intent: say "run this script" or "read this as reference" — never leave the agent to guess whether a bundled file is executable or illustrative
references/

Additional documentation loaded on demand. Keep individual files focused — agents load these when instructed, so smaller files save context.

  • Every file under references/ must be at or under 60,000 characters. When a reference grows past the cap, split it into focused files (e.g., references/<topic>-a.md, references/<topic>-b.md) and update SKILL.md so each new file is reachable and the load-on-demand instructions name the right file.
Show full SKILL.md (557 more words)Show less
assets/

Static resources: templates, images, data files, schemas.

evals/

Portable output-quality cases for the skill. New skills in this repository must include evals/evals.json with at least five cases; trigger-only checks belong in the harness-specific test set instead of this file.

File References

Use relative paths from the skill root when referencing other files:

markdown
See [the specification](references/specification.md) for details.

Run a bundled script:
scripts/<script-name>

Keep file references one level deep from SKILL.md. Avoid deeply nested reference chains.

Writing Effective Descriptions

The description field is the primary mechanism for automatic skill selection. Clients can also support explicit activation. Follow these principles:

  • Use imperative phrasing. "Use this skill when..." rather than "This skill does..."
  • Focus on user intent, not implementation. Describe what the user is trying to achieve.
  • Err on the side of being pushy. Explicitly list contexts where the skill applies.
  • Keep it concise. A few sentences to a short paragraph is right.

Best Practices

Start from real expertise

Feed domain-specific context into skill creation. Skills grounded in real project artifacts (runbooks, API specs, code review comments, actual failure cases) outperform ones synthesized from generic knowledge.

Spend context wisely

Focus on what the agent wouldn't know without the skill: project-specific conventions, domain-specific procedures, non-obvious edge cases. Don't explain general concepts the agent already knows.

Calibrate control
  • Give freedom when multiple approaches are valid — describe why, not just what
  • Be prescriptive when operations are fragile or a specific sequence must be followed
  • Match prescriptiveness to fragility: for a step that must be exactly right every time, prefer a deterministic script in scripts/ over instructions the agent improvises on each run. A test only catches what you already thought to check; a script takes the guess out of the loop entirely
  • Provide defaults, not menus — pick one approach, mention alternatives briefly
  • Favor procedures over declarations — teach how to approach a class of problems, not what to produce for one instance
Design coherent units

Scope skills like functions: one coherent unit of work that composes well with other skills. Too narrow → multiple skills needed for one task. Too broad → hard to activate precisely.

Use gotchas sections

The highest-value content is often environment-specific corrections — things the agent will get wrong unless told otherwise. When an agent makes a mistake, add the correction to the gotchas section.

Provide output templates

When output needs a specific format, provide a template inline or in assets/. Agents pattern-match well against concrete structures.

Adopting Third-Party Skills

Skills are executable capability: when a skill activates, its instructions and scripts run with the agent's permissions — shell access, file system, and credentials. Before running a skill you did not author (from a registry, a colleague, or an LLM generation), read vetting third-party skills and treat it like any other dependency: inspect provenance, read the body and every script, and check what the skill reaches out to.

Validation

Use the skills-ref reference library to validate skills:

bash
skills-ref validate ./my-skill

This checks that SKILL.md frontmatter is valid and follows all naming conventions.

For this repository, also run the bundled whole-repository checker:

bash
ruby scripts/validate-skills.rb

It checks canonical top-level and bundle skills for frontmatter, supported fields, line limits, local links, and required README sections. Vendored profile skills under agent-council/profiles/skills/ are intentionally excluded because they follow the source repository's conventions.

If skills-ref is unavailable, do not claim a successful validator run. Perform and report the equivalent structural checks manually, or install and run the reference validator when the task permits it.

© magnus919, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 11 other files (references) in agent-skills of magnus919/agent-skills.

  • SKILL.md
  • README.md
  • evals/evals.json
  • references/best-practices.md
  • references/client-implementation.md
  • references/evaluating-skills.md
  • references/home.md
  • references/optimizing-descriptions.md
  • references/quickstart.md
  • references/specification.md
  • references/using-scripts.md
  • references/vetting-third-party-skills.md

Open the folder on GitHubat commit 22b4723

Compare with similar skills

Agent Skills next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Agent Skills compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agent Skills this skillmagnus919/agent-skills115—~3kAutomated safety check: PassMIT
Bkit Exploreww-w-ai/bkit-claude-code601—~1.1kAutomated safety check: PassApache-2.0
LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs13k8 repos~3kAutomated safety check: PassMIT
Hugging Face Local Model Evalshuggingface/skills11k2 repos~1.6kAutomated safety check: PassApache-2.0
Looperksimback/looper710—~2.7kAutomated safety check: NotesMIT
Agent Eval Engineeringlangchain-ai/langchain-skills1.3k—~4kAutomated safety check: PassMIT

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Questions about Agent Skills

What does Agent Skills do?

A skill your agent uses when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client. Agent Skills is an agent skill from magnus919/agent-skills. Use this skill when creating, reviewing, or editing Agent Skills-format skills, or when implementing skill discovery and loading in an agent client.

When should I use Agent Skills?

Agent Skills fits situations like: editing Agent Skills-format skills; implementing skill discovery and loading in an agent client; general software work that does not involve the Agent Skills format.

How do I install Agent Skills in Claude Code?

Run `npx skills add magnus919/agent-skills --skill agent-skills -a claude-code`. Or copy the skill folder (agent-skills in magnus919/agent-skills) into .claude/skills/agent-skills in your project. Claude Code loads it when a task matches its description.

How do I install Agent Skills in Codex?

Run `npx skills add magnus919/agent-skills --skill agent-skills -a codex`. Or copy the skill folder (agent-skills in magnus919/agent-skills) into .agents/skills/agent-skills in your project. Codex loads it when a task matches its description.

Can I use Agent Skills in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add magnus919/agent-skills --skill agent-skills -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-skills, .gemini/skills/agent-skills, .github/skills/agent-skills and .opencode/skills/agent-skills in your project.

What does Agent Skills need to run?

Going by SKILL.md and its folder, Agent Skills needs the command-line tools its instructions call (ruby).

Does Agent Skills access the network?

SKILL.md names 2 domains. As links in the text: agentskills.io and github.com. This is read from the text; nothing was executed.

Is Agent Skills safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Agent Skills use?

Agent Skills is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Skills use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 31k tokens, read only when the agent opens those files.

What are the alternatives to Agent Skills?

Skills that share tags, products or a category with Agent Skills: Bkit Explore (ww-w-ai/bkit-claude-code, 601 stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), Hugging Face Local Model Evals (huggingface/skills, 11k stars) and Looper (ksimback/looper, 710 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Skills?

magnus919 (a GitHub user) maintains it in magnus919/agent-skills, which has 115 GitHub stars. The repository holds 131 skills in this directory. The repository was last updated on October 10, 2026.

Source: magnus919/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.