✓ Works with any AI agent

Stop babysitting
your AI agents.

OpenKit gives your AI agents a real workflow — pick up tasks, work in isolated environments, and ship pull requests. Like engineers, not interns.

Download OpenKit
Terminal
$ let's work on <task_id>
▶ Analyzing task...
▶ Creating worktree...
▶ Implementing...
▶ Verifying...
✓ Feature shipped!

From ticket to pull request. Autonomous.

A continuous story: capture work, execute in isolation, coordinate tooling, and ship with visibility and confidence.

  1. Issue Tracker
  2. Agents
  3. Validation
  4. Delivery

One Workflow. Many Surfaces.

OpenKit gives you a UI for setup, visibility, and day-to-day management, while the same workflow can run quietly in the background through one shared skill your agents already follow.

Work from any terminal or agent interface without changing how you or your team operates.

Spec-Driven Development

Everything starts with a real task. You define the work, and agents take care of execution with the context they need.

  • You create tasks, agents execute them.

    Your team sets priorities and intent, then OpenKit converts that into a clear execution queue so agents can keep moving without constant manual steering or repeated handoffs.

  • Connect Jira, Linear, and local tasks in one flow.

    External trackers and local tasks are handled consistently, so intake feels unified instead of split across tools, and teams can route work the same way regardless of source.

  • Task details, comments, and attachments are saved locally.

    Agents can use relevant context directly from local project data, including ticket updates over time, which reduces manual copy/paste and keeps execution stable as requirements evolve.

  • AI-targeted context and todos come first.

    You can add local instructions and task-specific todos for agents, and that guidance is prioritized during execution so work stays aligned with your team’s real implementation expectations.

Isolated Environments

Each task gets its own environment so agents can run in parallel without stepping on each other.

  • Each task gets a separate environment.

    Work for one task does not leak into another, so you can run multiple streams in parallel with clean boundaries and review outcomes independently before merging.

  • Agents stay fully isolated from each other.

    Every agent operates independently in its own workspace, avoiding collisions in code changes, process state, and runtime behavior even when several agents are active at once.

  • Built on Git worktrees under the hood.

    OpenKit uses native Git worktree mechanics to keep task branches physically separated while still tied to the same repository, making it easy to inspect and compare parallel work.

  • Independent runtime with automatic port conflict resolution.

    Each environment can run on its own, with port offsets applied automatically so parallel servers do not conflict and each task remains runnable without manual port debugging.

Agent Tooling Hub

Bring your AI stack under one roof with a centralized way to manage tooling across all projects.

  • Centralized AI tooling across projects.

    Manage how your agents are equipped from one place instead of repeating setup in every repo.

  • No more proprietary agent silos.

    Tooling and workflow configuration stop living in isolated agent-specific pockets and become reusable across your stack.

  • Automatic device-wide tool discovery.

    OpenKit scans what is already installed and helps you bring it into a single managed workflow quickly.

  • Hooks at defined workflow checkpoints.

    Agents can run configured checks at specific stages, so outcomes stay more predictable and stable from task start to delivery.

Real-Time Visibility

Follow the path from ticket to pull request in real time, and step in only when human input is needed.

  • Live activity feed for all agents in one place.

    You can track concurrent workstreams without switching views, so status stays visible as execution scales.

  • High-signal notifications for blockers and approvals.

    Important events are surfaced when attention is required, reducing noise while keeping critical moments clear.

  • Readable progress at high concurrency.

    Even with many active agents, activity remains understandable so teams can make quick decisions with confidence.

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