OpenChamber
Open-source workspace to run, supervise, and review AI coding work across desktop, browser, editor, and mobile.
Evidence shows: README mentions Private Relay end-to-end encryption, revocable, UI password protection, default localhost binding, security policy document lists sensitive data scope. But no code-level least privilege, user confirmation, data flow transparency implementation details. Dependency security has patch-package and overrides but no vulnerability scanning or audit evidence. External effects (tunnels, SSH) documented but not deep. Rollback not mentioned. Source attribution: README clearly states independent project, not affiliated with OpenCode, but no code provenance. Deductions: lack of concrete implementation evidence, rollback missing.
Evidence shows: README features align with package.json scripts, version consistent (1.18.2), but no test results or runtime verification. Dependency availability: uses bun and Node 22, but no lockfile or integrity checks. Failure messages: troubleshooting guide exists but no specific error handling code. Deductions: static review cannot verify runtime behavior, dependency availability evidence insufficient.
Evidence shows: README clearly targets developers/teams, scenarios cover desktop, web, mobile, CLI, environment fit (macOS, Windows, Linux, iOS, Android). Capability boundaries: features described but no explicit limits. Trigger precision: command examples (e.g., openchamber status) but not detailed. Environment fit: installation instructions and system requirements provided. Deductions: capability boundaries and trigger precision evidence insufficient.
Evidence shows: README structure clear, with quick start, guides, security, troubleshooting sections. Installation notes detailed (desktop, VS Code, CLI). Naming stability: version number clear, but no API stability statement. Examples and FAQ: command examples and guides, but no FAQ document. Known limitations: not explicitly listed. License: MIT license file present. Versioning changelog: no CHANGELOG file. Maintenance responsibility: SECURITY.md and contributing guide, but no explicit maintainer. Deductions: missing known limitations, changelog, maintainer info.
Evidence shows: Output usability: multiple interfaces (desktop, web, mobile) and features (multi-run, fusion, changes walkthrough). Marginal value: adds session management, remote access, scheduling over OpenCode. Cost-benefit: open-source free, but no performance or resource consumption data. Deductions: cost-benefit evidence insufficient.
Evidence shows: README feature descriptions align with package.json scripts and doc links, but no independent verification. Cross-source corroboration: Discord and GitHub links, but no third-party reviews. Fact-inference separation: README clearly distinguishes project from OpenCode, but no technical fact verification. Deductions: lack of independent verification and third-party corroboration.
- Static review cannot verify runtime behavior; all scores are inferred from documentation and code structure.
- No rollback mechanism provided; users need to backup or rely on version control.
- Dependency security lacks vulnerability scanning or audit evidence; recommend security review before use.
- No known limitations or changelog provided; users may encounter undocumented issues.
What does this agent do, and when should you use it?
OpenChamber is an open-source workspace for running, supervising, and reviewing AI coding work across desktop, browser, editor, and mobile. It is built on OpenCode and provides features like Session Goals, Multi-run, Fusion, Changes Walkthrough, Preview, GitHub integration, Private Relay, and scheduled tasks. The desktop bundle includes the OpenCode CLI and supports macOS, Windows, and Linux. It also offers Web/PWA, VS Code extension, iOS/Android apps, and a CLI/server version. Session Goals allow agents to work until a goal is met or a limit is reached, even after closing the app. Multi-run lets you compare up to five models in parallel, and Fusion combines the strongest parts. Changes Walkthrough turns large diffs into AI-guided step-by-step tours. Preview lets you inspect a running app and send element context to the agent. GitHub integration allows starting sessions from issues or PRs, sending feedback, and managing PRs. Private Relay provides end-to-end encrypted remote access via QR pairing.
OpenChamber runs and supervises OpenCode-based coding agents. It uses Session Goals to keep agents working until completion. Multi-run allows up to five models to work on the same task in parallel, and Fusion merges the best parts. Changes Walkthrough groups diff edits into steps and explains them. Preview opens an app and lets you send element screenshots, styles, position, and browser errors to the agent. GitHub integration starts sessions from issues/PRs, sends failed checks or review comments back, and updates or merges PRs. Private Relay pairs devices via QR code with end-to-end encryption. CLI commands include openchamber status, connect-url --qr, tunnel start, startup enable, logs, stop, and update.
- A frontend developer can start a session with a goal and let the agent modify code until tests pass, even after closing the laptop.
- A lead can use Multi-run to assign the same task to five models, compare their outputs, and pick the best one.
- A code reviewer can use Changes Walkthrough to understand a large diff as a guided step-by-step tour.
- A remote worker can start a session on desktop, then review and steer it from a phone or tablet away from the desk.
- A maintainer can start a session from a GitHub issue, have the agent work on it, and manage the resulting PR.
- An automation enthusiast can schedule recurring tasks with Session Goals, running prompts daily, weekly, or on a cron schedule.
What are this agent's strengths and limitations?
- Cross-platform support across desktop, Web, VS Code, iOS, and Android with synced project state.
- Session Goals allow agents to work autonomously toward a finish line without constant monitoring.
- Multi-run and Fusion enable parallel comparison of multiple models, improving decision quality.
- Private Relay provides end-to-end encrypted remote access without opening ports.
- Deep GitHub integration allows starting sessions from issue/PR context and managing PRs.
- Dependent on OpenCode CLI as the agent engine, and is an independent project not affiliated with OpenCode.
- CLI/Web requires Node.js 22+, which may be a constraint on legacy systems.
- Some features like Private Relay depend on network connectivity and external services like Cloudflare.
- Desktop bundles OpenCode, but CLI versions require manual installation, adding setup friction.
- Documentation is developer-oriented; non-technical users may face a learning curve.
How do you install or deploy this agent?
Desktop: Download the latest release from GitHub Releases for macOS, Windows, or Linux. For Linux, download the AppImage, make it executable (chmod +x OpenChamber-*.AppImage), and run it (./OpenChamber-*.AppImage). Linux AppImages require FUSE (libfuse.so.2); if unavailable, run with APPIMAGE_EXTRACT_AND_RUN=1. VS Code: Install 'OpenChamber' from the Visual Studio Marketplace. CLI/Web: Requires Node.js 22+ and an installed OpenCode CLI. Install with curl -fsSL https://raw.githubusercontent.com/openchamber/openchamber/main/scripts/install.sh | bash, then use openchamber commands.
How do you use this agent?
After installation, the first CLI run should set a UI password: openchamber --ui-password be-creative-here. Check status with openchamber status. Generate a connection QR with openchamber connect-url --qr. Start a Cloudflare tunnel with openchamber tunnel start --provider cloudflare --mode quick --qr. Enable startup with openchamber startup enable. View logs with openchamber logs. Stop with openchamber stop. Update with openchamber update. The desktop version includes a bundled OpenCode CLI, so no separate installation is needed.