Quickstart

This page gets you from install to a useful first Atomic session. Atomic is the loop engine for all engineering work: it runs reliable coding-agent loops with stages, tools, artifacts, verification, subagents, review gates, checkpoints, and human approvals.

Prerequisites

Node.js 24 LTS or newer — Atomic requires the latest Node LTS runtime. Check with node --version.
A package manager — use npm (included with Node), pnpm, Yarn, or Bun. Bun installs need Bun 1.3.14+.
Model-provider access — Use /login after startup. Supports provider subscriptions and APIs.

Install

Install the published package globally with npm, pnpm, or Bun: With npm:

npm install -g @bastani/atomic

With pnpm:

pnpm add -g @bastani/atomic

With Bun:

bun add -g @bastani/atomic

Atomic does not require package install scripts. If you want to disable dependency lifecycle scripts during the Atomic install, you can add --ignore-scripts to the install command.

Which runtime runs your workflows

How you install Atomic decides which runtime hosts it: a package-manager install runs under Node, while the standalone binaries are Bun-compiled and run under Bun. Authored workflows execute inside whichever host is active, so a workflow that reaches for a Bun.* global runs only under the standalone binary and fails with Bun is not defined under an npm install. Installing Bun separately does not change that — the npm install still runs on Node. Write workflow code against APIs both hosts provide, such as node:child_process and node:fs; see Workflows for the rule and worked examples.

Alpine and musl Linux archives

For Alpine Linux, use atomic-linux-x64-musl.tar.gz on x64 or atomic-linux-arm64-musl.tar.gz on arm64. These archives provide native search and PTY bindings. Install their runtime libraries with apk add --no-cache libgcc libstdc++, then see the Alpine and musl Linux archive notes for the clipboard fallback and external Postgres or Docker requirement for durable workflows. Then start Atomic in the project directory you want it to work on:

cd /path/to/project
atomic

Uninstall

Remove the global package with the same package manager you used to install it:

npm uninstall -g @bastani/atomic
pnpm remove -g @bastani/atomic
bun remove -g @bastani/atomic

This removes the CLI package only. User configuration, auth, sessions, and packages remain under ~/.atomic/agent/ unless you delete that directory yourself.

Authenticate

Atomic can use subscription providers through /login, or API-key providers through environment variables or the auth file. Start Atomic and run:

/login

Then select a provider. Built-in subscription logins include Claude Pro/Max, ChatGPT Plus/Pro (Codex), and GitHub Copilot.

Option 2: API key

Set an API key before launching Atomic:

export ANTHROPIC_API_KEY=sk-ant-...
atomic

You can also run /login and select an API-key provider to store the key in ~/.atomic/agent/auth.json. See Providers for all supported providers, environment variables, and cloud-provider setup.

First session

On a fresh install with no prior Atomic startup state, Atomic shows a one-time first-run explanation after any What’s New notes and directly above the input box describing Atomic as a verifiable coding agent runtime for building and running agent workflows you can feel confident in. Returning users with prior startup state are marked onboarded automatically and continue directly into the normal chat UI; stored credentials by themselves do not skip the first-run explanation. The composer is the normal Atomic input from the start: type a message, run /login first if no provider is connected, open /atomic, or launch a workflow command without a special onboarding transition. Once Atomic starts, default to a workflow for non-trivial work and for requests with inherent structure plus a verifiable objective. Implementation, build, debugging, bug fixes, migrations, features, scoped multi-file edits, validation/review work, and loop-shaped requests are workflow candidates; reserve direct chat for tiny deterministic low-risk answers or edits where tracking clearly adds more overhead than value. Workflow-first is not builtin-only or monolithic. Atomic can discover and run named builtin, project, user, and package workflows; author a rich custom TypeScript workflow({...}) inline; and compositionally import reusable workflow definitions—including builtins from @bastani/workflows/builtin—into parent workflows with ctx.workflow(...). Nested children can nest again within maxDepth, so custom graphs can combine proven research, implementation, design, verification, and approval workflows instead of copying them. They can also classify and branch, dynamically fan out and synthesize artifacts, run adversarial repair cycles, tournament-rank candidates, and loop until checks pass with explicit bounds. Atomic turns repeatable engineering loops into executable stages with inspectable evidence instead of relying on a markdown checklist the model may or may not follow. For an interactive tour any time, run /atomic inside the TUI; /atomic overview, /atomic workflows, and /atomic example walk through the same flow in more depth.

Try the built-in workflows

Atomic ships with nine workflows you can run immediately. Use /workflow list to see them and /workflow inputs <name> to inspect their inputs in your environment.

Workflow	When to use	Example
`classify-and-act`	Route requests through structured classification and low-confidence human fallback.	`/workflow classify-and-act prompt="Triage and handle this request"`
`fan-out-and-synthesize`	Partition independent slices, including repository-focused research, and synthesize their artifact evidence.	`/workflow fan-out-and-synthesize prompt="Map payment retries by subsystem and synthesize cited findings"`
`adversarial-verification`	Challenge a candidate with fresh verifiers and bounded repair.	`/workflow adversarial-verification task="Verify the migration patch"`
`generate-and-filter`	Generate, dedupe, filter, optionally judge, and shortlist candidates.	`/workflow generate-and-filter prompt="Propose names for the new command"`
`tournament`	Compare whole solutions through balanced pairwise judging.	`/workflow tournament prompt="Design the retry strategy"`
`loop-until-done`	Iterate with a durable ledger until completion or bound exhaustion.	`/workflow loop-until-done prompt="Repair failures until the test suite passes"`
`goal`	Autonomous work that needs a durable ledger, bounded sub-agent orchestration, receipts, and reviewer-gated completion.	`/workflow goal objective="Update the CLI docs, add one example, and validate the docs build"`
`ralph`	Research-first autonomous work with prompt refinement, delegated implementation, and iterative multi-model review.	`/workflow ralph prompt="Implement specs/rate-limit.md and validate burst traffic"`
`open-claude-design`	UI and design-system work with one generated preview, one live review session, and export.	`/workflow open-claude-design prompt="Refresh the settings page hierarchy as a page"`

Workflow List

Inputs are bare key=value tokens. Values are JSON-parsed when possible, so count=5, flag=true, and prompt="multi word value" preserve useful types. If you call /workflow <name> without required inputs, the TUI opens an inline picker; pass --no-picker to skip it. Goal and Ralph support git_worktree_dir only when you explicitly want a reusable worktree, and skip PR creation unless you set create_pr=true for the post-approval final stage. You can also launch workflows with natural language — describe the task in chat and ask Atomic to run a matching installed workflow or author a task-specific one:

Fan out repository research by subsystem, save cited findings as artifacts, and synthesize the evidence.

Create a worker → fresh verifier → reducer workflow that updates the CLI docs, runs the docs build, and repairs evidence-backed findings until it passes or reaches a bounded stop.

Use goal to update the CLI docs, include one example, run the docs build, and finish only when reviewers approve the evidence.

Use ralph to research and implement specs/rate-limit.md, then review and repair it within three loops.

Atomic chooses a complete execution shape, fills inputs from the request, and confirms before launch. Use Goal when a durable ledger and receipt-backed reviewer gate fit the task. Use Ralph when the job benefits from a research-first implementation/review loop. For exact domain contracts that either builtin does not cover, author a custom graph with deterministic checks and bounded repairs.

Monitor and steer a run

Named workflow runs execute in the background. After launch you get the full run id; user-facing workflow surfaces show that complete UUID. You can still type the full id or a unique short prefix to inspect, connect, pause, quit, or resume a run. Ambiguous prefixes are reported rather than selecting a run arbitrarily.

/workflow status <run-id>         # inspect one run's progress
/workflow status                  # list this session's active and terminal runs
/workflow connect <run-id>        # see agents working; chat with or steer each stage (F2 also opens latest)
/workflow attach <run-id> <stage> # chat with one stage
/workflow interrupt <run-id>      # pause resumably
/workflow resume <run-id> "go"    # send a steer message and resume
/workflow quit <run-id>           # pause gracefully and keep the run resumable

The below-editor BACKGROUND panel uses two lines per card at 80 columns and wider: the status glyph and full id are on the first line, and the workflow name plus mode/progress/elapsed metadata are on the second. Below 80 columns it collapses to a count-only line. In chat surfaces, a full id wraps onto continuation lines at narrow widths instead of being cut, and the surrounding border remains intact. Human-in-the-loop prompts (ctx.ui.input, confirm, select, editor) surface in the graph viewer, not as chat modals — connect to the run to answer them. Atomic also posts main-chat lifecycle notices when a run completes, fails, or awaits input. If you answer a workflow prompt in the graph or attached stage chat, the main chat receives a display-only answer summary for audit; it does not wake the model, enter LLM context, or answer later prompts. See Workflows for the full reference and authoring guide.

Top skills to invoke directly

Skills are reusable expert instructions. Trigger one with /skill:<name> followed by a request:

Skill	When to use	Example
`research-codebase`	Scoped research that writes a grounded artifact for one subsystem or question.	`/skill:research-codebase how the rate limiter works in src/middleware/`
`create-spec`	Turn research into an implementation-ready plan.	`/skill:create-spec from research/docs/2026-03-rate-limit.md`
`prompt-engineer`	Create, optimize, evaluate, or troubleshoot prompts for GPT-5.6, Claude Opus 5, and Claude Fable 5.	`/skill:prompt-engineer Draft a sharper repo-research prompt for payment retries end to end.`
`tdd`	Test-first feature or bug work.	`/skill:tdd`
`impeccable`	Critique or refine web/native frontend and product UI; includes detector hooks, framework-aware live review, and mount-failure recovery.	`/skill:impeccable`
`playwright-cli`	Drive a real browser for end-to-end UI checks, screenshots, and reviewable proof videos.	`/skill:playwright-cli`
`liteparse`	Pull text, tables, or values out of PDF, DOCX, PPTX, XLSX, and image files locally.	`/skill:liteparse`

Impeccable 4.1.1 resolves Live sessions to the selected app root, supports SvelteKit, Nuxt, TanStack Start, Astro, Next.js, Vite, and static HTML injection, and rejects absolute, traversing, or symlinked configured write targets. Its concept roll may contact impeccable.style; set IMPECCABLE_NO_TELEMETRY=1 or DO_NOT_TRACK=1 to disable the anonymous choice ping. The image fallback runs only with OPENAI_API_KEY, sends prompts and optional reference images to OpenAI, and spends that account’s API credit. Generated image prompts are embedded in the image or a sidecar, so do not include secrets. Use /skill:research-codebase for a focused subsystem or question. For repository-wide research, use fan-out-and-synthesize with distinct repository partitions and an artifact synthesis barrier. Use Goal for ledger-backed bounded orchestration and Ralph for research-first delegated implementation with iterative review; task size alone does not select either workflow.

Create your own workflow in natural language

Named workflows may be builtin, project, user, or package supplied. You do not have to hand-write TypeScript to add a new workflow. Describe what you want in plain chat and Atomic will design and write it for you using the Workflows reference as the source of truth:

Create a reusable Atomic workflow called review-changes. It takes one
required text input `target` (a diff, PR, or review focus). Run two reviewers
in parallel with fresh context — one for correctness and missing tests, one
for edge cases and maintainability — then a synthesis stage that
consolidates findings into blockers vs. suggestions and returns
{ consolidated_review, decision }.

Atomic will:

ask clarifying questions if stage purpose, inputs, models, or handoffs are ambiguous,
write a .atomic/workflows/<name>.ts definition that uses workflow({ ... }) and imports Type from typebox,
run /workflow reload so the generated workflow is rediscovered and can be launched with /workflow <name>,
then report the generated workflow folder so you can inspect the code it wrote, using Custom workflow created. You can inspect its code at: <workflow-folder-path> (for example, .atomic/workflows/); Atomic does this only for newly created custom workflows, never builtin or pre-existing workflows.

The same plain-chat approach works for editing or hardening an existing workflow. For the full authoring reference, see Workflows, including composition with user-defined workflows and all nine builtins from @bastani/workflows/builtin.

Default tools and prompts

If you’d rather start with a plain prompt, just type a request and press Enter:

Summarize this repository and tell me how to run its checks.

By default, Atomic gives the model these tools:

read - read files
bash - run shell commands
edit - patch files
write - create or overwrite files
find - discover files by glob pattern
search - search file contents
ask_user_question - ask structured questions in the TUI
todo - manage file-based todos

Normal coding sessions include file discovery and content search through find and search in addition to read, bash, edit, and write. Atomic runs in your current working directory and can modify files there. Use git or another checkpointing workflow if you want easy rollback.

Give Atomic project instructions

Atomic loads context files at startup. Add an AGENTS.md file to tell it how to work in a project:

# Project Instructions

- Run `bun run typecheck` after code changes.
- Do not run production migrations locally.
- Keep responses concise.

Atomic loads:

~/.atomic/agent/AGENTS.override.md, AGENTS.md, or CLAUDE.md for global instructions (legacy ~/.pi/agent/ also works)
AGENTS.override.md, AGENTS.md, or CLAUDE.md from parent directories and the current directory

An AGENTS.override.md file replaces the other context files in its directory. Restart Atomic, or run /reload, after changing context files.

Common things to try

Reference files

Type @ in any interactive editor to fuzzy-search files; or pass files on the command line:

atomic @README.md "Summarize this"
atomic @src/app.ts @src/app.test.ts "Review these together"

Images can be pasted with native macOS Cmd+V, Ctrl+V (Alt+V on Windows), or dragged into supported terminals. Inside tmux on macOS, use Ctrl+V for reliable image paste; native Cmd+V depends on terminal forwarding. VS Code’s terminal may forward the empty bracketed-paste route through tmux, while Ghostty may not forward its Kitty super+v route through tmux. When the clipboard has both text and an image, Ctrl+V prefers the image; Cmd+V may paste text or the image depending on how the terminal delivers the gesture.

Run shell commands

In interactive mode:

!bun run lint

The command output is sent to the model. Use !!command to run a command without adding its output to the model context.

Switch models

Use /model or CTRL+L to choose a model. Use SHIFT+Tab to cycle thinking level. Use CTRL+P / SHIFT+CTRL+P to cycle through scoped models.

Continue later

Sessions are saved automatically:

atomic -c                  # Continue most recent session
atomic -r                  # Browse previous sessions
atomic --name "my task"    # Set session display name at startup
atomic --session <path|id> # Open a specific session

Inside Atomic, use /resume, /new, /tree, /fork, and /clone to manage sessions.

Non-interactive mode

For one-shot prompts:

atomic -p "Summarize this codebase"
cat README.md | atomic -p "Summarize this text"
atomic -p @screenshot.png "What's in this image?"

Use --mode json for JSON event output or --mode rpc for process integration.

Next steps

Using Atomic - interactive mode, slash commands, sessions, context files, and CLI reference.
Workflows - run, inspect, and author multi-stage automation (including the built-in workflows).
Skills - reusable expert instructions invoked with /skill:<name>.
Providers - authentication and model setup.
Settings - global and project configuration.
Keybindings - shortcuts and customization.
Atomic Packages - install shared extensions, skills, prompts, and themes.

Platform notes: Windows, Termux, tmux, Terminal setup, Shell aliases.

Start here

Customization

Reference

Programmatic Usage

Platform Setup

Development

Changelog

Quickstart

Quickstart

Prerequisites

Install

Which runtime runs your workflows

Alpine and musl Linux archives

Uninstall

Authenticate

Option 2: API key

First session

Try the built-in workflows

Monitor and steer a run

Top skills to invoke directly

Create your own workflow in natural language

Default tools and prompts

Give Atomic project instructions

Common things to try

Reference files

Run shell commands

Switch models

Continue later

Non-interactive mode

Next steps

​Quickstart

​Prerequisites

​Install

​Which runtime runs your workflows

​Alpine and musl Linux archives

​Uninstall

​Authenticate

​Option 1: subscription login

​Option 2: API key

​First session

​Try the built-in workflows

​Monitor and steer a run

​Top skills to invoke directly

​Create your own workflow in natural language

​Default tools and prompts

​Give Atomic project instructions

​Common things to try

​Reference files

​Run shell commands

​Switch models

​Continue later

​Non-interactive mode

​Next steps

Quickstart

Prerequisites

Install

Which runtime runs your workflows

Alpine and musl Linux archives

Uninstall

Authenticate

Option 1: subscription login

Option 2: API key

First session

Try the built-in workflows

Monitor and steer a run

Top skills to invoke directly

Create your own workflow in natural language

Default tools and prompts

Give Atomic project instructions

Common things to try

Reference files

Run shell commands

Switch models

Continue later

Non-interactive mode

Next steps