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Documentation Index

Fetch the complete documentation index at: https://bastani.mintlify.app/llms.txt

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Why not markdown, a coding agent alone, or a general agent framework?

Markdown is great for guidance: conventions, commands, repo notes. Use Claude Code, OpenCode, or Copilot CLI directly for normal single-session coding. Reach for Atomic at the point where the work needs branching, retries, parallel sessions, explicit state, human approval, sandboxed execution, or reliable handoff between stages. General agent frameworks can do some of this, but you often rebuild coding-agent basics yourself: file editing, terminal interaction, MCP setup, hooks, session handling, repo-specific context. Atomic starts from production coding agents and adds the workflow layer around them.

How does Atomic differ from Spec-Kit?

Spec-Kit is GitHub’s spec-driven development toolkit. Spec-Kit works well for greenfield projects with a single Copilot session. Atomic is built for the harder case — large existing codebases where you research first, with multi-session pipelines, isolated context windows, deterministic execution, and support for Claude Code, OpenCode, and Copilot CLI.
AspectSpec-KitAtomic
FocusGreenfield, spec-firstLarge existing codebases — research-first or spec-first
Workflow definitionShell scripts + markdownTypeScript Workflow SDK with deterministic execution
Session managementSingle agent sessionMulti-session pipelines, sequential and parallel, in isolated context windows
Agent supportGitHub Copilot CLIClaude Code + OpenCode + Copilot CLI
Sub-agents / skillsSingle general agent / none12 specialized sub-agents + 57 built-in skills
Autonomous executionNot availableRalph — multi-hour autonomous plan/implement/review/debug loop

How does Atomic differ from DeerFlow?

DeerFlow is ByteDance’s general-purpose agent runtime on LangGraph. DeerFlow is a general-purpose agent system with a web UI; Atomic is narrowly focused on coding workflows. Atomic runs on top of production coding agents (Claude Code, OpenCode, Copilot CLI) rather than reimplementing coding tools through a generic API — you get each agent’s native file editing, permissions, MCP integrations, and hooks out of the box.
AspectDeerFlowAtomic
RuntimePython (LangGraph)TypeScript (Bun)
Agent SDKsOpenAI-compatible APIClaude Code + OpenCode + Copilot CLI native SDKs
ExecutionDAG with conditional edgesDeterministic — strict step ordering, frozen definitions, controlled transcript passing
Sub-agentsResearcher / coder / reporter12 specialized sub-agents with scoped tools
InterfaceWeb UI (Streamlit)Terminal chat with tmux session management
AutonomousNot availableRalph — bounded plan/implement/review/debug loop

How does Atomic differ from Hermes Agent?

Hermes Agent is Nous Research’s general-purpose AI assistant with a self-improving learning loop. Hermes is a broad personal assistant that learns across sessions; Atomic is coding-specific workflow software for engineering teams. Atomic encodes your dev process as deterministic TypeScript workflows that run identically across teammates, machines, and CI, and inherits production-hardened tools from Claude Code, OpenCode, and Copilot CLI (giving you two independent security boundaries: devcontainer + agent permissions).
AspectHermes AgentAtomic
FocusPersonal AI assistant (coding + messaging + smart home)Coding-specific multi-session workflows for teams
RuntimePythonTypeScript (Bun)
Agent SDKsOpenAI-compatible adapterClaude Code + OpenCode + Copilot CLI native SDKs
ExecutionSingle conversation loop with context compressionMulti-session pipelines, fresh context per session, controlled transcript passing
SkillsAuto-created (may drift)57 developer-authored, version-controlled skills
ReproducibilityDifferent paths each runFrozen workflow definitions run identically across machines and CI
SecurityCommand approval + container backendsDevcontainer isolation + coding agent permission systems (two independent boundaries)