Summarize Workflow-tool fleet runs from the Agent Monitor — these fleets emit no hooks and are ingested from on-disk run journals. List recent runs with status and agents-per-run, then drill into a single run's per-agent detail. Reconciles against the live run-state endpoints. Use when reviewing Workflow() fleets rather than hook-instrumented interactive sessions.
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Summarize Workflow-tool (Workflow()) fleet runs and drill into one run's agents.
The user provides: $ARGUMENTS
latest → drill into the most recent run.These fleets emit no hooks; the dashboard ingests them from on-disk Workflow-tool run journals, so this data is independent of the hook event stream.
| Endpoint | Returns |
|---|---|
GET /api/workflows/runs | List of ingested fleet run journals: run id, status, agent count, timing |
GET /api/workflows/runs/{runId} | One run in detail: per-agent status, timing, type, and outputs |
GET /api/run | Live run state across the fleet (current/active runs) |
GET /api/run/{id} | Live state for one run, to reconcile against the journal |
| Run ID | Status | Agents | Started | Duration |
|---|---|---|---|---|
Sort most recent first. Add a one-line status mix below (e.g. 8 runs: 5 completed, 2 running, 1 error). |
latest is given)From GET /api/workflows/runs/{runId}, reconciled with GET /api/run/{id}:
| Agent | Type | Status | Duration | Notes |
|---|
Completion rate (completed / total agents), any stalled or errored agents, and whether the journal and the live run-state endpoint agree (flag drift if they do not).
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Inspect fired CCAM alerts and manage alert rules for token thresholds, event patterns, inactivity, and status duration. Use when acknowledging alerts, creating or editing a rule, checking cooldowns, or connecting alert rules to webhook targets.
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Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).
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Produce a detailed report on APIError events from Agent Monitor data — counts over time, which sessions and models are affected, and the likely root cause (rate limits, overload/529, or context-window pressure) inferred from each event's summary and data payload. Use when API errors spike or when you need to explain why requests are failing.
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Benchmark one session (or a small recent set) against the rolling average using Agent Monitor data — cost, total tokens, tool count, and workflow complexity score — and report where each metric lands as a percentile of the population. Tells you whether a session was normal, cheap, or an outlier. Use when judging whether a session was typical or out of band.
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Define a spend budget for Claude Code and, optionally, create a cost alert rule that fires when usage crosses the limit, via POST /api/alerts/rules on the Agent Monitor dashboard. Reads current spend from /api/pricing/cost to size the budget sensibly and explains every rule field before writing. Use when setting a spend limit or wiring up a budget guardrail.
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Analyze prompt-cache effectiveness for Claude Code usage from the Agent Monitor dashboard — cache hit rate (total_cache_read / (total_cache_read + total_input)), cache_write vs cache_read reuse, cache-read vs cache-write spend, and the sessions with the poorest reuse. Pulls token totals from /api/analytics, per-session detail from /api/sessions, and dollar splits from /api/pricing/cost. Use when diagnosing cache spend or deciding whether prompt caching is paying off.
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