Files
fusion/packages/cli
gsxdsm 7d9d097acf fix(cli): the TUI board fell back to the LEGACY workflow — it rendered a triage lane the default no longer has (#3178)
Found by following an unexplained number rather than by a sweep: while
re-verifying #3141 the resolver reported `intake: "todo"` where
`BUILTIN_CODING_WORKFLOW_IR` resolves `intake: "triage"`. That
divergence is correct and intentional inside core — and wrong here.

## The defect

`dashboard.ts` resolved a task's columns as `def?.ir ??
BUILTIN_CODING_WORKFLOW_IR`, and its card-chip fields the same way. That
constant is the **legacy** monolithic IR (`builtin:legacy-coding`); the
catalog's actual default is `resolveDefaultWorkflowIr()`. Post-U11 they
differ **by a whole column**:

```
default  todo, in-progress, in-review, done, archived          (planning merged into todo)
legacy   triage, todo, in-progress, in-review, done, archived
```

So a task with **no workflow selection row** was rendered against a
six-column board including `triage` — a lane the real default no longer
declares.

## The same drift is already documented as fixed elsewhere

`builtin-workflows.ts` records it:

> `prepareWorkflowMovePolicyPreflightImpl` resolved the default through
the catalog while `resolveTaskWorkflowIrForMove` used the raw constant,
so a task with NO selection row produced two different workflow
signatures and every flag-ON move threw *"workflow move policy preflight
is stale"*. Both sides (and the sync resolver) now call this helper so
the default cannot drift again.

This surface was missed, and it is the **last non-test consumer of the
legacy constant outside core**.

## Test scope, stated because it is narrow

Driving the TUI end-to-end needs a rendered terminal and a live store.
That harness does not exist here, and building one to assert a fallback
would be testing the harness. So the test pins the two facts that make
the bug possible and the fix meaningful:

1. **the two IRs genuinely disagree, about `triage` specifically** — if
a future change re-merges them, this reports it rather than leaving the
fix silently pointless;
2. **the source no longer reaches for the legacy constant.**

(2) is a source assertion, weaker than driving the code. It is used for
the same reason as the `FloatingWindow` aria-label scan: the defect is a
**value at a call site**, there is no single render that reaches both
sites, and a per-site render test would pin the one someone bothered to
write. Both assertions are anti-vacuity guarded — the IR comparison
fails if either side stops resolving to a v2 column set.

## Verification

| | result |
|---|---|
| cli `tsc` | **0 errors** |
| new test | **2 passed** |
| mutation — restore `?? BUILTIN_CODING_WORKFLOW_IR` | **1 failed / 2**
|
| census `--strict`, `check-fnxc-future-dates` | exit 0 (this class is
invisible to the census — an argument, not a comparison) |

Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-07-31 08:13:57 -07:00
..
2026-06-10 18:06:51 -07:00
2026-07-26 18:11:47 -07:00

Fusion

@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


Fusion reel: from rough idea to production code

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 install runfusion/fusion/fusion

Fully-qualified install auto-taps and, on Homebrew 6.0+, trusts only this formula. If short-name install fails with “untrusted tap”, run brew trust --formula runfusion/fusion/fusion then brew install 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.

Fusion mesh: laptop, Mac mini, Linux server, cloud VM, phone — all synced

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
Fusion agent company: import a team, run it autonomously for weeks

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:

  1. Install the droid binary and ensure it is on your PATH
  2. Authenticate with Droid CLI (droid auth login)
  3. In Fusion dashboard, go to Settings → Authentication and enable Factory AI — via Droid CLI
  4. 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.