Coldtea
Agentic development environment that unifies coding agents, visual QA testing, and production monitoring for end-to-end software delivery.
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Product Overview
What is Coldtea?
Coldtea is an agentic development environment built for teams that already rely on coding agents such as Claude Code, Codex, Gemini CLI, and OpenCode to write software. Rather than focusing only on how fast code gets written, Coldtea covers the rest of the delivery loop: a shared terminal for orchestrating multiple agents, visual QA agents that turn plain-English user journeys into self-healing tests, and monitoring agents that watch production logs, sessions, and feedback to open pull requests with investigated fixes. It runs locally next to your repository using your own shell, agents, and settings, with cloud execution available only when explicitly enabled, and syncs tasks to your existing engineering board so background agents can run work in parallel without tying up your machine.
Key Features
Unified Agent Terminal
Orchestrate multiple coding agents like Claude Code, Codex, Gemini CLI, and OpenCode side by side, with shared context so they can plan, build, and review work together while you stay in control.
Agentic Visual QA
Describe web and mobile user journeys in plain English and let QA agents convert them into self-healing tests that run against every PR preview and gate deployments automatically.
Self-Driving Production Monitoring
Always-on monitoring agents scan error logs, customer feedback, and user sessions, diagnose issues, and open pull requests with investigated fixes rather than raw alerts.
Cloud Task Execution
Assign engineering tasks to background agents running on hosted machines, run several in parallel, and review pull request results from a single dashboard.
Codebase Debt Sweeping
Agents continuously scan the codebase for technical debt that builds up when most code is agent-written, filing it directly onto the team's task board.
Local-First Architecture
Runs on your own machine next to your repo using your existing shell and agent settings, keeping code local by default while offering optional cloud runs.
Use Cases
- AI-Assisted Development Teams : Engineering teams running multiple coding agents can coordinate their work, review changes, and keep output synced in one shared workspace.
- Release Regression Testing : QA and dev teams can automate end-to-end regression checks on every pull request without hand-writing brittle test scripts.
- Production Incident Response : Ops and engineering teams can catch and diagnose production issues before users report them, cutting time-to-fix.
- Distributed Engineering Workflows : Teams can offload long-running or parallel tasks to cloud agents while keeping local development unaffected.
- Technical Debt Management : Teams shipping large volumes of agent-generated code can track and prioritize accumulating debt automatically.
FAQs
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