hoangsonww Concurrency Report
Report on parallel execution for one Claude Code session: lanes, peak width, utilization, and where work serialized.
Input
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.
Data Sources
| 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) |
Report Sections
1. Parallelism Summary
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
2. Lane Timeline
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.
3. Utilization
| Lane | Busy time | Idle time | Utilization % |
|---|---|---|---|
| Plus an overall utilization figure (busy lane-time / total lane-time). |
4. Serialization Bottlenecks
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.
Output
- Markdown tables for utilization; a fenced list for the lane timeline.
- Durations in human units (e.g.
48s,2m 10s); percentages to whole numbers. - Use ▲/▼ when comparing utilization against an even-distribution baseline.
- Cite only timing returned by the API; never invent lane overlaps or durations.
- If the session ran a single agent (no concurrency), say so plainly rather than inventing lanes.
- If the dashboard is unreachable, tell the user to start it with
npm startfrom the repo root.