57dc91585d
Internal SmartGift build of a Claude Code monitoring dashboard. Lanes: a durable unit of parallel agent work, one per working directory, tracked across session restarts. Managed lanes are git worktrees the dashboard provisions and can reset or remove behind a three-check destroy guard and a counted preflight; adopted lanes are directories you already own and are never destroyable. Pipelines: a lane moves through pipeline stages. A stage the agent declares with evidence renders green; a stage inferred from the tool-event stream renders dashed amber and never counts as done. Detection is forward-only within a 30-minute window, and never writes the declared stage. Workspace: one page at /run with a lane grid, the selected lane's pipeline, and a full Claude console behind a disclosure.
26 lines
1.3 KiB
Markdown
26 lines
1.3 KiB
Markdown
---
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description: Print the orchestration DAG edges (parent→child subagents) for a session.
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argument-hint: "[session-id]"
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---
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Print the multi-agent orchestration DAG for a session from `http://localhost:4820`.
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The session id is **$ARGUMENTS**. If empty, fetch `curl -s 'http://localhost:4820/api/sessions?limit=1'` and use the most recent session, stating which id you picked. If the dashboard is unreachable, tell the user to start it with `npm start` from the repo root.
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Fetch the workflow intelligence and read its `orchestration` dataset:
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```
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curl -s http://localhost:4820/api/workflows/$ARGUMENTS
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```
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`orchestration` contains the DAG nodes (agent id, type, model, status, depth) and parent→child edges.
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Print, concisely:
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1. **One-line topology** — `root → depth <N>, fan-out <max>, <agent count> agents`.
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2. **Edge list** — one line per edge, grouped/ordered by depth:
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`depth d: parent[model] → child[type, status]`
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3. **Leaves** — list the leaf agents (no children) on one line.
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No tables, no preamble — just the topology line and the edges. Cite only nodes and edges returned by the API; never invent agents. If the session has no subagents, say so (single-agent session, depth 0). For a rendered tree and depth/fan-out breakdown, point the user at the `dag-map` skill.
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