Atomic can create skills. Ask it to build one for your use case.

Skills

Skills are self-contained capability packages that the agent loads on-demand. A skill provides specialized workflows, setup instructions, helper scripts, and reference documentation for specific tasks. Atomic implements the Agent Skills standard, warning about violations but remaining lenient.

Locations
How Skills Work
Skill Commands
Skill Structure
Frontmatter
Validation
Example
Skill Repositories

Locations

Security: Skills can instruct the model to perform any action and may include executable code the model invokes. Review skill content before use.

Atomic loads skills from:

Global:
- ~/.atomic/agent/skills/ (legacy ~/.pi/agent/skills/)
- ~/.agents/skills/
Project (only after the project is trusted):
- .atomic/skills/ (legacy .pi/skills/)
- .agents/skills/ in cwd and ancestor directories (up to git repo root, or filesystem root when not in a repo)
Packages: skills/ directories, atomic.skills, or legacy pi.skills entries in package.json
Settings: skills array with files or directories
CLI: --skill <path> (repeatable, additive even with --no-skills)

Discovery rules:

In ~/.atomic/agent/skills/ and .atomic/skills/ (plus legacy ~/.pi/agent/skills/ and .pi/skills/), direct root .md files are discovered as individual skills when they have valid skill frontmatter with a non-empty description
In all skill locations, directories containing SKILL.md are discovered recursively
In ~/.agents/skills/ and project .agents/skills/, root .md files are ignored
Root Markdown files other than SKILL.md that do not look like skills are ignored silently

Disable discovery with --no-skills (explicit --skill paths still load).

Using Skills from Other Harnesses

To use skills from Claude Code or OpenAI Codex, add their directories to settings:

{
  "skills": [
    "~/.claude/skills",
    "~/.codex/skills"
  ]
}

For project-level Claude Code skills, add to .atomic/settings.json (legacy .pi/settings.json is also supported):

{
  "skills": ["../.claude/skills"]
}

How Skills Work

At startup, Atomic scans skill locations and extracts names and descriptions
The system prompt includes available skills in XML format per the specification
When a task matches, the agent uses read, or bash when read is unavailable, to load the full SKILL.md (models don’t always do this; use prompting or /skill:name to force it)
The agent follows the instructions, using relative paths to reference scripts and assets

This is progressive disclosure: only descriptions are always in context, full instructions load on-demand.

Built-in prompt engineering guidance

The bundled /skill:prompt-engineer creates, optimizes, evaluates, and troubleshoots prompts for GPT and Claude models. Its small routing file points to separate, source-attributed guides for GPT-6 Astra, GPT-5.6, GPT-5.5, Claude Fable 5.1, Claude Fable 5, Claude Opus 5, Claude Opus 4.8, and Claude Sonnet 5. Read the target model’s page, or both relevant pages for a migration, without loading every guide. Shared references cover prompt structure, tools, evaluation, and instruction audits; model defaults, effort, verification, and API compatibility stay in their own pages. Astra guidance distills OpenAI’s model guide into completion and permission rules, proportionate verification, useful parallel delegation, concise writing, and API migration checks. An instruction audit based on Eric Provencher’s advice explains how to shorten skill descriptions, use small routing files with optional references, remove obsolete recipes, and define safe local work and stopping points. It preserves binding repository requirements and separates API features from capabilities actually exposed by the host. The skill no longer recommends response prefilling, which returns an error on Claude 4.6 and later, or visible chain-of-thought as a primary technique. Use explicit output instructions, schemas, tools, or post-processing instead of prefilling. Request conclusions, citations, commands, and observed results rather than reconstructed private reasoning; such requests can trigger Claude Fable 5’s reasoning_extraction safeguard and force a model fallback.

Built-in visual explanation guidance

The bundled /skill:show-me from HumanLayer helps explain the current topic visually with concise diagrams, code-shape sketches, and focused HTML artifacts. It is distributed under the MIT License.

Built-in code quality guidance

The bundled /skill:qlty runs code-quality verification through the qlty CLI, which drives 70+ linters, auto-formatters, and security scanners across 40+ languages: qlty check for linting, qlty fmt for auto-formatting, qlty metrics for complexity, lines, and cohesion, and qlty smells for duplication, deep nesting, and overly complex code. It triggers on requests for verifiers or high code quality and prefers one CLI over ad-hoc per-tool linter invocations. The skill directs the agent to docs.qlty.sh/llms.txt as the authoritative documentation index, tells it to enable the qlty plugins and linter extensions that fit the codebase before checking, and ships source-attributed reference excerpts beside SKILL.md. The CLI is not bundled; install it with curl https://qlty.sh | bash (macOS and Linux) or powershell -c "iwr https://qlty.sh | iex" (Windows), and keep ~/.qlty/bin on PATH. Note that qlty init writes .qlty/qlty.toml into the repository. Offline, qlty metrics and qlty smells still work (built-in static analysis); qlty check and qlty fmt download plugins and runtimes on first use per repository and need network then.

Skill Commands

Skills register as /skill:name commands:

/skill:brave-search           # Load and execute the skill
/skill:pdf-tools extract      # Load skill with arguments

When multiple real skill files declare the same name, Atomic keeps the existing precedence winner for the bare command and retains every distinct file as an exact candidate. Use a source-qualified command to select one explicitly:

/skill:review                  # Current precedence winner
/skill:review@project          # Unique project candidate
/skill:review@user             # Unique user candidate
/skill:review@builtin          # Unique bundled candidate

@project, @user, and @builtin are available only when that family has one candidate in the collision. If a family contains multiple package candidates, Atomic advertises package-qualified aliases instead, such as /skill:review@team-review and /skill:review@company-review; the family selector is ambiguous and reports the exact choices. Autocomplete, pi.getCommands(), and RPC get_commands return the same advertised names. Qualified selection is exact. An unknown or ambiguous qualified selector reports an error and never falls back to the bare winner. Aliases are recalculated on reload, so a qualified alias disappears when its collision disappears. The model-visible skill list uses the same aliases, while the opaque candidate IDs stored in transcripts and collision diagnostics are internal identity, not command names. Subagent definitions and per-call skills overrides accept these same selectors. Live in-process children resolve them from their own loader catalog after resource reload; a missing or ambiguous selector is reported in the child result instead of silently selecting the bare skill. The parent-only subagent orchestration skill cannot be injected into a child, including qualified aliases such as subagent@builtin. Extensions can read the same catalog through ctx.getSkillCatalog(). Arguments after the command are appended to the skill content as User: <args>. Toggle skill commands via /settings in interactive mode or in settings.json:

{
  "enableSkillCommands": true
}

Skill Structure

A skill is a directory with a SKILL.md file. Everything else is freeform.

my-skill/
├── SKILL.md              # Required: frontmatter + instructions
├── scripts/              # Helper scripts
│   └── process.sh
├── references/           # Detailed docs loaded on-demand
│   └── api-reference.md
└── assets/
    └── template.json

SKILL.md Format

---
name: my-skill
description: What this skill does and when to use it. Be specific.
---

# My Skill

## Setup

Run once before first use:
```bash
cd /path/to/skill && bun install
```

## Usage

```bash
./scripts/process.sh <input>
```

Use relative file paths from the skill directory (these are bundled skill files, not docs routes):

See the API reference at `references/api-reference.md` for details.

Keep authored instructions outcome-first and concise. State observable completion and stop conditions, give a short reason for material constraints, and use decision rules for judgment calls instead of ALWAYS/NEVER language. Put detailed or model-specific material in references/ so it loads only when needed. Do not ask models to reproduce private reasoning or repeatedly verify their own work; require evidence or validation results where correctness matters.

Frontmatter

Per the Agent Skills specification:

Field	Required	Description
`name`	Yes	Max 64 chars. Lowercase a-z, 0-9, hyphens. Must match parent directory.
`description`	Yes	Max 1024 chars. What the skill does and when to use it.
`license`	No	License name or reference to bundled file.
`compatibility`	No	Max 500 chars. Environment requirements.
`metadata`	No	Arbitrary key-value mapping.
`allowed-tools`	No	Space-delimited list of pre-approved tools (experimental).
`disable-model-invocation`	No	When `true`, skill is hidden from system prompt. Users must use `/skill:name`.

Name Rules

1-64 characters
Lowercase letters, numbers, hyphens only
No leading/trailing hyphens
No consecutive hyphens
Must match parent directory name

Valid: pdf-processing, data-analysis, code-review Invalid: PDF-Processing, -pdf, pdf--processing

Description Best Practices

The description determines when the agent loads the skill. Be specific. Good:

description: Extracts text and tables from PDF files, fills PDF forms, and merges multiple PDFs. Use when working with PDF documents.

Poor:

description: Helps with PDFs.

Validation

Atomic validates skills against the Agent Skills standard. Most issues produce warnings but still load the skill:

Name doesn’t match parent directory
Name exceeds 64 characters or contains invalid characters
Name starts/ends with hyphen or has consecutive hyphens
Description exceeds 1024 characters

Unknown frontmatter fields are ignored. Declared skills with missing descriptions are not loaded. Malformed SKILL.md files and SKILL.md files without a description produce warnings and are not loaded. Other Markdown files without valid skill frontmatter are ignored. Name collisions (the same name from different real files) produce diagnostics and keep the existing first-winner precedence for /skill:name. Atomic also retains the other files as source-qualified candidates as described in Skill Commands.

Example

brave-search/
├── SKILL.md
├── search.js
└── content.js

SKILL.md:

---
name: brave-search
description: Web search and content extraction via Brave Search API. Use for searching documentation, facts, or any web content.
---

# Brave Search

## Setup

```bash
cd /path/to/brave-search && bun install
```

## Search

```bash
./search.js "query"              # Basic search
./search.js "query" --content    # Include page content
```

## Extract Page Content

```bash
./content.js https://example.com
```

Skill Repositories

Anthropic Skills - Document processing (docx, pdf, pptx, xlsx), web development
Pi Skills - Upstream skill examples for web search, browser automation, Google APIs, and transcription

Start here

Customization

Reference

Programmatic Usage

Platform Setup

Development

Changelog

Skills

Skills

Table of Contents

Locations

Using Skills from Other Harnesses

How Skills Work

Built-in prompt engineering guidance

Built-in visual explanation guidance

Built-in code quality guidance

Skill Commands

Skill Structure

SKILL.md Format

Frontmatter

Name Rules

Description Best Practices

Validation

Example

Skill Repositories

​Skills

​Table of Contents

​Locations

​Using Skills from Other Harnesses

​How Skills Work

​Built-in prompt engineering guidance

​Built-in visual explanation guidance

​Built-in code quality guidance

​Skill Commands

​Skill Structure

​SKILL.md Format

​Frontmatter

​Name Rules

​Description Best Practices

​Validation

​Example

​Skill Repositories

Skills

Table of Contents

Locations

Using Skills from Other Harnesses

How Skills Work

Built-in prompt engineering guidance

Built-in visual explanation guidance

Built-in code quality guidance

Skill Commands

Skill Structure

SKILL.md Format

Frontmatter

Name Rules

Description Best Practices

Validation

Example

Skill Repositories