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Get Started Free →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.
.claude/skills/hoangsonww-concurrency-report/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-09 | ✗→✓ | ▲ Improved | -46% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 150% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -51% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -25% | 0% |
| case-15 | ✗→✓ | ▲ Improved | 136% | 0% |
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.
48s, 2m 10s); percentages to whole numbers.npm start from the repo root.Other measured skills in the registry, with their headline benchmark lift.