96b2df115e
## Windows: local runtime hung at "Starting local Fusion runtime…"
### Root cause
Desktop startup had two independent persisted sources of truth that
could disagree:
- `desktop-launch-mode.json` — decides whether **main** *starts* the
embedded local runtime
- `shell-connections.json` (`desktopMode`) — decides whether the
renderer **launch gate** *waits* for it
`shell:setDesktopMode` persists shell settings **before** the fallible
`startLocalRuntimeOnce()` / `saveDesktopLaunchMode()`. So a first
"local" selection whose runtime start threw or was interrupted left
`shell=local` / `launch-mode=choose` **permanently**. Every later launch
then sat at "Starting local Fusion runtime…" polling a runtime nobody
started → 30s timeout.
### Fix (defense in depth) — `78f0bc31`
- `initializeApp` reconciles: a completed shell `local` selection is
authoritative → heals the launch-mode file and starts the runtime.
- `onDesktopModeChange` / `onDesktopLaunchModeChange` persist
launch-mode **before** the fallible start so it can't re-desync.
- `DesktopLaunchGate` no longer assumes main started the runtime — if
it's not running/starting it actively `setDesktopMode("local")` before
polling.
- Env-gated startup trace (`FUSION_STARTUP_TRACE`) so packaged builds
(which log nothing) are diagnosable.
- Regression tests: split-brain → runtime starts + file heals;
agreement-on-choose → no start.
**Verified end-to-end under real Electron 35 / Node 22.16**: from the
exact split-brain state the runtime now reaches `RUNNING` and the
launch-mode file heals.
### Also: Windows root-build breakages — `bd24bd4c8`
- `scripts/build-workspace.mjs` "run as main" guard compared
`import.meta.url` to `` `file://${process.argv[1]}` ``, which never
matches on Windows → root `pnpm build` silently no-opped (exit 0, no
dist). Now uses `pathToFileURL(process.argv[1]).href`.
- `spawn('pnpm', …)` without `shell:true` (ENOENT on Windows) in
`build-workspace.mjs` and `packages/cli/tsup.config.ts` → pass `shell`
on win32.
### Notes
- `@fusion/desktop` and `@fusion/dashboard` are private → no changeset.
- Build the Windows installer via the `desktop-windows` workflow
(`electron-builder --projectDir deploy`); local `pnpm deploy` staging
hits an unrelated directory-rename race on managed-workspace
filesystems.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **New Features**
* Added optional desktop runtime startup tracing (enabled via
environment variable).
* **Bug Fixes**
* Improved local desktop handoff to prevent reload loops and navigate
directly to the embedded local runtime.
* Added “split-brain” healing between persisted launch mode and shell
settings.
* Prevented auto-registration of runtime root/CWD during
desktop/dashboard startup.
* Improved Windows compatibility for CLI/workspace command spawning and
npm install process handling.
* **Tests**
* Expanded local/Electron integration, navigation, and onboarding
regression coverage; improved async flushing for more reliable
initialization.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
@runfusion/fusion
From rough idea to production code — automatically.
Multi-node agent orchestrator — tasks, agents, missions, git, files, and worktrees, with any model, local or cloud.
runfusion.ai → · GitHub · Docs
Install
Zero install, straight from npm:
npx runfusion.ai
Boots the dashboard. Subcommands forward through (npx runfusion.ai task list, etc). Long form: npx @runfusion/fusion dashboard.
One-line installer (macOS & Linux — auto-picks Homebrew, falls back to npm):
curl -fsSL https://runfusion.ai/install.sh | sh
Homebrew (macOS & Linux):
brew tap runfusion/fusion
brew install fusion
Or as a one-liner: brew install runfusion/fusion/fusion.
npm global:
npm install -g @runfusion/fusion
fn dashboard # or: fusion dashboard
Launch the dashboard
From a shell:
fn dashboard # or: fusion dashboard / npx @runfusion/fusion dashboard
fn dashboard --paused # start with automation paused
fn dashboard --dev # development-mode dashboard + AI engine
fn dashboard --no-engine # web UI only, no AI engine
The dashboard gives you:
- A live kanban board — tasks move through columns automatically as AI works on them
- Task detail view — generated spec, step-by-step progress, reviewer verdicts, full execution log
- Dependency-aware scheduling — declare task dependencies or let the engine infer them
- Auto-merge — on by default; reviewed work squash-merges without you lifting a finger
- Parallel execution — independent tasks run simultaneously in isolated git worktrees
- Self-sustaining board — agents may spawn follow-up tasks; the board feeds itself
Your entire dev environment. On a single pane of glass.
Describe a task in plain language. A triage agent reads your project, understands context, and writes a full PROMPT.md spec — steps, file scope, acceptance criteria. Then Fusion plans, reviews, executes, and reviews again, in an isolated git worktree, with a human approval gate wherever you want one.
One board. Controlled from anywhere. Laptop, Mac mini, Linux server, cloud VM, phone — all connected.
Run an agent company
Import a team. Run it autonomously for weeks. 440+ agents across 16 companies, wired for missions, mailboxes, and inter-agent delegation.
npx companies.sh add paperclipai/companies/gstack
How it works
You create a task with a rough description. A pipeline of specialized agents takes over.
Specification. A triage agent reads your codebase — file structure, existing patterns, related code — and turns your rough idea into a detailed spec. It breaks the work into discrete steps, identifies which files are in scope, writes acceptance criteria, and assigns a complexity rating that determines how aggressively the work gets reviewed.
Scheduling. Tasks declare dependencies on each other. The scheduler builds a dependency graph and starts work only when upstream tasks are done. Independent tasks run in parallel — each in its own isolated git worktree, so there are no conflicts during execution.
Execution & review. An executor agent works through the spec step by step in the worktree. At each step boundary, a separate reviewer agent, with read-only access, independently evaluates the work. The reviewer can approve (continue), request revisions (fix specific issues), or force a rethink (change the approach entirely). Review depth scales with the task's complexity rating: trivial tasks get light checks, complex tasks get thorough multi-pass review.
Merge. When execution finishes and the reviewer signs off, the task moves to In Review:
- Direct merge (default) — automatically squash-merges the completed task branch into your current branch with a clean commit.
- Pull request — automatically creates or links a GitHub PR, waits for reviews/checks, then merges once policy conditions are satisfied.
autoMerge controls whether Fusion performs completion automatically. If disabled, tasks stay in In Review until you finish the merge yourself. For PR-first mode, authenticate GitHub with gh auth login.
Tasks flow through: Triage → Todo → In Progress → In Review → Done.
This execution model is heavily based on Taskplane.
What makes it different
| 🧠 AI specification | Rough idea in, detailed PROMPT.md out — steps, file scope, acceptance criteria. |
| 🔁 Workflow gates | Plan → Review → Execute → Review on every step. Block or pass automatically. |
| 🌳 Worktree isolation | Each task runs in its own branch and worktree. Parallel tasks. Zero conflicts. |
| ⚡ Smart merge | Passing every gate? Fusion squash-merges and moves on. |
| 🛰️ Multi-node mesh | Laptop, server, cloud, phone — all synced. Desktop, mobile, web. |
| 🧩 Any model | Anthropic, OpenAI, Ollama, and more. |
| 🏢 Agent companies | Import pre-built teams — 440+ agents across 16 companies. |
| 📬 Inter-agent messaging | Built-in mailbox between agents. Delegate, clarify, coordinate. |
| 🗺️ Missions | Hierarchical planning with autopilot and validation contracts. |
| 🔓 Open source. MIT. | No vendor lock-in. Run it on your own hardware. |
Working from chat
Manage tasks without leaving the conversation:
"Every ten minutes, analyze the server code for logic the client hasn't implemented yet and create tasks. Tasks may spawn additional tasks, so just add enough to keep the board saturated."
"Create a Fusion task to fix the login redirect bug"
"Add a task for dark mode support, it depends on FN-003"
"What's the status of FN-042"
"Attach screenshot.png to FN-007"
"Pause FN-012 — I want to add more context first"
The Fusion extension exposes tools to create tasks, check progress, attach files, and pause or resume automation.
Standalone CLI
See STANDALONE.md for additional installation and usage options.
Optional provider: Factory AI via Droid CLI
@runfusion/fusion now ships a vendored @fusion/droid-cli extension in the published CLI bundle.
To use it:
- Install the
droidbinary and ensure it is on yourPATH - Authenticate with Droid CLI (
droid auth login) - In Fusion dashboard, go to Settings → Authentication and enable Factory AI — via Droid CLI
- Restart Fusion when prompted so the extension is loaded into the runtime
Once enabled, droid-cli models appear in Fusion model selection.
Maintainer note: workspace plugins in published CLI bundles
When CLI or dashboard runtime code imports workspace plugin packages (for example @fusion-plugin-examples/roadmap), those imports must stay statically analyzable and covered by packages/cli/tsup.config.ts noExternal rules so plugin runtime code is inlined into dist/bin.js.
Do not introduce dynamic or variable module specifiers for workspace plugin runtime paths in the published execution path. If a workspace plugin is needed for bundled auto-install, stage a bundled plugin entry (dist/plugins/<id>/bundled.js) rather than copying raw TypeScript source into dist/.
Full documentation
Architecture details, development setup, and contributor info live in the project README.
License
MIT — see LICENSE.