nntrivi2001
17d56d0e01
Clean break, no compatibility alias. Renames the product name, the CLI binary (`ccam` -> `agenthub`), the env var prefix (`CCAM_` -> `AGENTHUB_`), the Prometheus metric namespace (`ccam_*` -> `agenthub_*`), the tmux session prefix (`ccam-lane-<id>` -> `agenthub-lane-<id>`), the per-repo runtime profile directory (`.ccam/profile` -> `.agenthub/profile`), the lanes state root (`~/.claude/ccam-lanes` -> `~/.claude/agenthub-lanes`), the bundled plugins (`plugins/ccam*` -> `plugins/agenthub*`) and their slash commands (`/ccam-doctor` -> `/agenthub-doctor`, `/ccam:*` -> `/agenthub:*`). Because there is no alias, an existing install has to be updated by hand: rename its `.ccam/profile` directory and any `CCAM_*` variables, and reinstall the plugin under its new name. Two other name families are deliberately left alone here, since they are not just strings: the `Claude-Code-Monitor` repository/marketplace name, and the `agent-dashboard` npm package plus its `~/.claude/agent-dashboard` runtime directory, which holds the live database and needs a migration rather than a rename. Verified: server 1406/1406, client 459/459, `grep -i ccam` clean across tracked files, `openapi.yaml` regenerated (95 paths, unchanged count).
2.5 KiB
description
| 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. |
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.