tasktrooper

Website: tasktrooper.ai · Docs: tasktrooper.ai/docs · Download: Releases

A local-first agent platform for software teams of one. A board of tasks, a set of role agents (product manager, architect, backend, frontend, QA), and a runtime that hands each task to Claude Code (or another agent CLI) on your own machine — clone, plan, implement, test, open the PR — while you watch the run.

Everything runs on your Mac: the desktop app starts an embedded Postgres and the Go backend, serves the UI, and runs the agent sessions locally. No account, no cloud, no login.

You don't drive the agents, the board does. Put a task on the board and the agent that owns its column picks it up on its own, does the work and hands the task on to the next column, where the next agent takes over. Nobody has to press run.

A usage limit doesn't lose work. When Claude Code runs out of its usage limit in the middle of a task, the agent stops and the task waits on Blocked. Once the limit resets, TaskTrooper resumes the same Claude Code session, so the agent carries on from where it stopped instead of starting over.

Features

Board

• A Kanban board with thirteen columns out of the box, from Backlog to Released, including analysis review, code review, QA, PM UAT and human UAT. The columns, and which agents pick up work in each, are configurable.
• Agents take tasks by themselves. A task that lands in a column is dispatched to that column's agent automatically and moves on when the agent is done.
• Tasks carry acceptance criteria. A task cannot move forward out of a review column until every criterion has a verdict.
• Tasks can block each other; a blocked task waits until its blocker is done.
• Every task gets its own branch and pull request. Code review reads the PR, Done merges it, and Done and Released watch the deploy and can roll it back.
• When Claude Code hits its usage limit, the task is parked on Blocked until the limit resets. Then it resumes by itself with claude --resume on the parked session, so the agent keeps what it already read and wrote and continues from where it stopped.

Role agents

Six agents ship with a library of 95 seeded skills plus rules. They run on Claude Code with sonnet by default and opus for subtasks rated hard.

Every agent is editable: provider and model, tool policy, effort, skills, rules, the columns it works, and its memory. You can chat with any agent directly, or about a specific task.

• Your own agents. Create an agent from a template or from scratch with its own prompt, skills, rules, tool policy, columns and memory, and save any agent as a template for the next one.
• One board, several CLIs. The runtime is chosen per agent, not per install. A developer on Claude Code, a reviewer on the Cursor CLI, a QA agent on OpenCode and an API-only agent on Gemini can all work the same board, each in its own session.

Self-evolution

Agents rewrite their own playbooks from how their work actually went.

• Reflection. On a schedule, whenever a task is sent back to Need Revision, or on demand, an agent reviews everything since its last reflection: its runs, chat messages, revision comments, scores, KPI results and its current skills, rules and memories. It proposes changes to all three. Skill and rule changes are applied only for agents with self-evolution turned on.
• Golden gate. With the gate enabled, a golden task suite runs before and after a proposed change, and an independent judge model decides whether to keep it. If the pass rate drops, the whole change set is reverted automatically.
• Impact tracking. Each applied change is later classified as effective, regressed or neutral by comparing scores before and after it. Regressions are put in front of the agent's next reflection, which decides whether to revert.
• Budgets and history. Skills and rules are capped per agent (25 and 15 by default), so an agent merges and updates instead of piling up. Every write to a skill or rule is versioned with its source (you, self-evolution or the seed) and any version can be restored.
• KPIs. Each agent has targets such as tasks completed, first-pass rate, revisions received, UAT failures, failed runs and time spent per column, measured per day, week or month. The targets are part of the agent's prompt, and the Performance page shows how it is doing.

Memory and code understanding

• Agents save and search memories in four scopes: personal or team-wide, for one repository or for every repository. Notes about a single run are refused, and a near-duplicate is not saved twice.
• Repositories are parsed with tree-sitter and embedded on your machine with the bundled nomic-embed-text-v1.5 model, so agents search code semantically and see uncommitted edits without a re-index.
• Skills are loaded on demand, so a long skill list does not fill the prompt.
• Files uploaded to a workspace are available to agents through retrieval.

Runtimes, models and tools

• Agent CLIs run as local processes: Claude Code, Cursor, Antigravity and OpenCode. A Claude Code session gets TaskTrooper's board tools over MCP with a per-run token, and never loads a repository's .mcp.json or your personal Claude Code settings.
• API providers for agents that do not use a CLI: OpenAI, Anthropic, Google Gemini, Groq, or any OpenAI-compatible endpoint such as LM Studio, Ollama or vLLM.
• Connect your own MCP servers.
• Built-in tools: terminal, file editing, web search with no API key, page fetch, headless-browser QA, and a boilerplate catalog to start new projects from.
• A repository's own version pins (.tool-versions, go.mod, .nvmrc and others) are honoured in the agent session.

Integrations and operations

• GitHub: clone, branches, pull requests, review comments, merge, and CI status from GitHub Actions.
• Deploys: a recipe catalog for Google Cloud Run and GKE, AWS ECS and Lambda, Vercel and Fly, rendered into a workflow per environment with a health check, plus a deployment matrix. A Vercel account can be connected to bind existing projects.
• Production incidents: alerts from Alertmanager, Sentry, Cloud Monitoring or any JSON webhook, together with a health monitor, fold into deduplicated incidents with a suggested remedy: a rollback, a config, dependency or capacity fix, or a code defect. Per repository you choose whether an incident is only recorded, becomes a diagnosis task, or is fixed through the board.
• Mobile releases: connect App Store Connect and Google Play and promote builds through internal, external and production channels. QA can drive iOS simulators and Android emulators on this Mac through Appium.
• Usage: token usage per model and per day.

First run

A guided setup checks this Mac (git, the agent CLIs you have, and optionally Chrome, Xcode, Appium and the Android SDK), lets you connect any of Claude Code, Cursor, Antigravity and OpenCode, or an API provider with your own key, then connects GitHub and imports your first project.

Install

curl -fsSL https://raw.githubusercontent.com/makifbaysal/tasktrooper/main/scripts/install.sh | bash

It downloads the latest release's universal .dmg, copies TaskTrooper into /Applications, and prints the commands for anything else you need. Pass -y to replace an existing install without being asked.

With Homebrew once this repository is public; the repository is its own tap:

brew tap makifbaysal/tasktrooper https://github.com/makifbaysal/tasktrooper
brew install --cask tasktrooper

The app is ad-hoc signed and not notarized yet, so a copy you install by hand may need right-click → Open the first time; the install script and the cask both clear the quarantine flag for you.

First launch downloads two things into the app's data directory: the Postgres binaries (~30 MB) and the embedding model (~140 MB). You need git and at least one way to run agents: the Claud