debug-live-issue
Debug production-like issues in this repository with disciplined evidence gathering. Use when fixing failing workflows, regressions, flaky behavior, or data…
Report concurrency and parallelism for a session — how many agents ran in parallel, concurrency-lane utilization, peak parallel width, and serialization bottlenecks (sequential chains that could have run as parallel lanes) — using the Agent Monitor workflow intelligence API. Use
$ npx -y skills add hoangsonww/Claude-Code-Agent-Monitor --skill concurrency-report --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/concurrency-reportContext preview
The summary Claude sees to decide when to auto-load this skill.
Report concurrency and parallelism for a session — how many agents ran in parallel, concurrency-lane utilization, peak parallel width, and serialization bottlenecks (sequential chains that could have run as parallel lanes) — using the Agent Monitor workflow intelligence API. Use
name: concurrency-report description: > Report concurrency and parallelism for a session — how many agents ran in parallel, concurrency-lane utilization, peak parallel width, and serialization bottlenecks (sequential chains that could have run as parallel lanes) — using the Agent Monitor workflow intelligence API. Use when checking whether a multi-agent session used parallelism efficiently.
Report on parallel execution for one Claude Code session: lanes, peak width, utilization, and where work serialized.
The user provides: **$ARGUMENTS**
A session ID. If empty, fetch `GET /api/sessions?limit=1` and report on the most recent session, stating which one.
| Endpoint | Returns | |----------|---------| | `GET /api/workflows/{sessionId}` | The `concurrency` dataset (overlapping agent execution lanes with start/end timing) and the `complexity` dataset (numeric score from depth, breadth, and tool diversity) |
From `concurrency`: number of distinct lanes, peak parallel width (max agents running simultaneously), and total agents. Pair with the `complexity` score to judge whether the parallelism matched the work's size. `Lanes: N · Peak parallel: M · Agents: K · Complexity: S`
A per-lane list of the agents that occupied each lane in order: `Lane 1: explore (0–12s) → code-review (12–48s)` `Lane 2: debugger (5–30s)` Show overlapping windows so simultaneity is visible.
| Lane | Busy time | Idle time | Utilization % | |------|-----------|-----------|---------------| Plus an overall utilization figure (busy lane-time / total lane-time).
Identify sequential chains where one agent waited on the previous despite no apparent dependency — candidates to run as parallel lanes. State the chain and the wall-clock time it cost. Only flag chains the `concurrency` timing data actually shows as sequential.
🚀 A real-time monitoring dashboard for Claude Code & Codex, built with SQLite3, Node.js, Express, React, Vite, TailwindCSS, & WebSockets. It tracks sessions, agent activity, tool usage, and subagent orchestration, providing live analytics, a Kanban status board, status notifications, a cute buddy, & an interactive web UI/MacOS/Windows native app.
Repo: hoangsonww/Claude-Code-Agent-Monitor
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