AGENT SKILL

workflow-monitor

Use when you want to LIVE-monitor a Claude Code Workflow ("ultracode") fan-out — watch every parallel agent's status, lens/task, model, tokens, tool activity, and final result across the WHOLE FLEET (all sessions/projects) in a read-only terminal cockpit, instead of the sparse native /workflows view or opening a terminal-tail per agent. Also for triaging errored/retrying/stalled agents mid-run, or reviewing a finished run's per-agent prompt/output.

License 许可
MIT
最近更新
2026-11-02
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01 前言 Front Matter

name
workflow-monitor
description
Use when you want to LIVE-monitor a Claude Code Workflow ("ultracode") fan-out — watch every parallel agent's status, lens/task, model, tokens, tool activity, and final result across the WHOLE FLEET (all sessions/projects) in a read-only terminal cockpit, instead of the sparse native /workflows view or opening a terminal-tail per agent. Also for triaging errored/retrying/stalled agents mid-run, or reviewing a finished run's per-agent prompt/output.

02 资源文件 6

03 SKILL.md 正文

workflow-monitor

Overview

A live, read-only, Windows-native Textual cockpit for Claude Code Workflow (ultracode) runs. It surfaces the one signal the native /workflows view and the old per-agent tailers under-use: the live-flushed telemetry manifest ~/.claude/projects/<proj>/<sess>/workflows/wf_<id>.json (re-written ~0s after every agent progress event), which already carries per-agent label (the human lens name), phase, model, state, tokens, tool activity, and prompt/result previews — for the whole fan-out, across every session/project.

Run it

pip install textual rich          # one-time (textual is the only non-stdlib dep)
python workflow_monitor.py        # the interactive whole-fleet cockpit
python workflow_run.py            # a plain-text one-shot fleet board (no TUI) — quick check / CI-friendly

Cockpit: left = filter + status chips + a run → phase → agent tree (glyph · lens · model · tokens · last-tool; ↻ retry, STALL Ns when idle); right = the selected agent's Task (its prompt), a live Feed (transcript tail), and Result (headline + clean output). Keys: q quit · f live-follow · r refresh. It never writes any .claude file and polls O(changed) so it stays snappy across hundreds of runs.

How it works

workflow_run.py is the shared, dependency-light parser (manifest + journal + transcripts + FleetPoller O(changed) polling); the recall-workflow-agent skill shares this same core. Output/status come from the authoritative journal result / started events, not mtime guessing.

Export a run (e / wfmon export)

Caveat (important)

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