agentleFS
JordanHoodJordanHood/claude-skills/skills/dispatch-dashboard/SKILL.md

dispatch-dashboard

Skill0 starsChanged 8 months agoMITView on GitHub

Live browser dashboard for monitoring dispatch workers. Shows real-time progress, blocked workers, IPC questions, and auto-shuts down when all tasks complete. Launch via script or include in dispatch scaffolding.

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Start the dashboard server pointing at a dispatch tasks directory:

    line 17
  2. Distinctive:

    Add to the dispatch scaffolding Bash call:

    line 30

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Dispatch Dashboard

Live browser dashboard for monitoring dispatch worker progress.

Usage

Start the dashboard server pointing at a dispatch tasks directory:

python3 <skill-dir>/scripts/dashboard.py <tasks-dir> [--no-open]
  • <tasks-dir>: path to .dispatch/tasks/ directory
  • --no-open: skip auto-opening browser

The server binds to a free port on localhost, writes the port to .dispatch/dashboard.port, and opens the dashboard in your browser.

Integration with Dispatch

Add to the dispatch scaffolding Bash call:

if [ ! -f .dispatch/dashboard.port ] || ! curl -s -o /dev/null -w '' "http://localhost:$(cat .dispatch/dashboard.port)/api/status" 2>/dev/null; then
  rm -f .dispatch/dashboard.port .dispatch/dashboard.pid
  python3 <skill-dir>/scripts/dashboard.py .dispatch/tasks &
fi

Auto-Shutdown

The server monitors for .done markers in each task's IPC directory. Once all tasks have completed, it waits 60 seconds (grace period for reviewing final state) then exits and cleans up port/pid files.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.