TAKT
Stop babysitting AI coding agents.
TAKT is an open-source CLI that turns AI coding agents into repeatable development workflows. Define planning, implementation, review, fix loops, human checkpoints, permissions, and output contracts in YAML, then run tasks with isolated worktrees and traceable logs.
Instead of asking one agent to remember the whole process, TAKT gives each step its own role, context, and transition rules. Agents can code, but the workflow decides what happens next.
- Run plan → implement → review → fix loops as explicit workflow steps
- Keep context focused with step-specific personas, policies, knowledge, instructions, and output contracts
- Execute queued tasks in isolated worktrees and inspect logs and reports afterward
- Use Claude Code, Claude SDK, Codex SDK, OpenCode SDK, Pi SDK, the official DeepSeek Harness SDK, Cursor, GitHub Copilot CLI, or Kiro as providers
TAKT Agent Koordination Topology orchestrates multiple AI agents with review loops, managed prompts, and per-step permissions.
Talk to AI to define what you want, queue it as a task, and run it with takt run. Planning, implementation, review, and fix loops are defined in YAML workflow files, so the process is not left to the agent's discretion. TAKT coordinates Claude Code, Codex, OpenCode, Pi, the official DeepSeek Harness SDK, Cursor, GitHub Copilot CLI, and Kiro CLI as agents with different roles, permissions, and context.
TAKT is built primarily for AI coding workflows, but the same model applies beyond coding: any task where multiple AI agents need to coordinate, or where review, judgment, and feedback loops can improve task quality.
TAKT is built with TAKT itself (dogfooding).
Why TAKT
AI coding agents do not automatically create a stable development process. In long-running work, they forget instructions, accumulate polluted context, blur implementation and review responsibilities, and often force humans to repeat the same feedback again and again.
Adding more rules to prompts, CLAUDE.md, or skills can help, but it cannot enforce the process. Whether the rules are followed is still left to the agent's behavior.
TAKT treats AI agents as something to be controlled from the outside, not simply trusted.
Workflows define the phases, and each step receives its own persona, policy, knowledge, instruction, and output contract. TAKT manages implementation, review, fix, and re-review flows declaratively. By separating responsibilities, knowledge, and constraints, then giving each agent only what it needs for the current step, TAKT improves task quality without bloating context.
Reviews cannot be silently skipped. Findings route work back to fix steps, and human judgment can be requested when needed. Tasks run in isolated worktrees, and each step leaves logs and reports so the path from task to PR remains traceable.
TAKT runs all of this as a reusable agent process built from roles, phases, judgments, and feedback loops, so the development process stays reviewable and reproducible without constant human intervention.
Try It in 5 Minutes
From a Git repository with at least one commit:
npm install -g takt
# Talk to AI, describe a task, use /go, then choose "Queue as task"
takt
# Execute queued tasks in isolated worktrees
takt run
# Review diffs, merge, retry, requeue, or delete task branches
takt list
If this is your first run, configure a provider in ~/.takt/config.yaml or use the API key environment variables listed in Configuration. SDK-based providers such as claude-sdk, codex, opencode, and pi can run with Node.js; deepseek-harness additionally requires Python 3.10+ and its official runtime wheel; CLI-based providers require their external CLIs.
Video Tutorial
Follow the written tutorial with these hands-on walkthroughs:
| Chapter 1 | Chapter 2 |
|---|---|
 |
 |
TAKT vs Plain AI Coding Agents
| Plain AI coding agents | TAKT |
|---|---|
| The prompt asks the agent to follow a process | The YAML workflow owns the process |
| Review steps can be forgotten or skipped | Review and fix loops are explicit transitions |
| One long context keeps growing | Each step receives only the context it needs |
| Implementation and review responsibilities blur | Personas, permissions, and output contracts separate responsibilities |
| Work often lands directly in the current tree | Queued tasks run in isolated worktrees by default |
| The path from task to result is hard to audit | Logs and reports preserve the path from task to PR |
| The same process must be recreated by memory | Workflows are reusable, reviewable, and versionable |
Requirements
TAKT requires Node.js >=22.22.0.
The provider you choose determines whether you need to install an external CLI or can run on Node.js alone via a TypeScript SDK.
These providers run via SDK (no CLI required, Node.js only):
claude-sdk—@anthropic-ai/claude-agent-sdkcodex—@openai/codex-sdkopencode—@opencode-ai/sdkpi—@earendil-works/pi-coding-agent
The deepseek-harness provider uses the official Python SDK through a private JSON-RPC bridge. Install the matching SDK/runtime packages with Python 3.10+:
python3 -m pip install deepseek-harness-sdk deepseek-harness-runtime-bin
The official runtime currently supports Linux x64/arm64 and macOS arm64 only. Windows and macOS x64 fail fast; TAKT does not silently fall back to another provider. Set DEEPSEEK_API_KEY and optionally DEEPSEEK_BASE_URL in the environment. The Python SDK and bundled deepseek-harness-runtime-bin must come from matching releases. This provider is a developer-preview compatibility surface: upstream API/event vocabulary may change between matching releases, so use the opt-in live smoke procedure in the configuration guide before relying on a new SDK/runtime pair.
These providers require an external CLI:
claude— Claude Codeclaude-terminal— Claude Code driven in an interactive terminal session (also requirestmux)copilot— GitHub Copilot CLIcursor— Cursor Agentkiro— Kiro CLI
Optional:
- GitHub CLI (
gh) — fortakt #N(GitHub Issue tasks) - GitLab CLI (
glab) — for GitLab Issue/MR integration (auto-detected from remote URL)
OAuth usage: Whether OAuth is permitted varies by provider and use case. Check each provider's terms of service before using TAKT.
Quick Start
Install
npm install -g takt
With Nix flakes:
nix run github:nrslib/takt
nix profile install github:nrslib/takt
The Nix package installs the TAKT CLI itself. External CLI providers, git, and gh/glab still need to be installed and available on PATH or configured separately as described in Requirements.
Talk to AI and queue tasks
$ takt
Select workflow:
❯ 🎼 default (current)
📁 🚀 Quick Start/
📁 🛠️ Development/
📁 🔍 Review/
> Add user authentication with JWT
[AI clarifies requirements and organizes the task]
> /go
Proposed task:
...
What would you like to do?
Execute now
Create GitHub Issue
❯ Queue as task # ← normal flow
Continue conversation
Choosing "Queue as task" saves the task to .takt/tasks/. Run takt run to execute — TAKT creates an isolated worktree, runs the workflow (plan → implement → review → fix loop), and offers to create a PR when done.
# Execute queued tasks
takt run
# You can also queue from GitHub Issues
takt add #6
takt add #12
# Execute all pending tasks
takt run
"Execute now" runs the workflow directly in your current directory without worktree isolation. Useful for quick experiments, but note that changes go straight into your working tree.