Trace the full event chain for one Claude Code session into an ordered timeline of every event type with tool_name and summary, highlighting gaps, out-of-order events, and failures. Reads /api/events?session_id= and /api/sessions/:id from the Agent Monitor dashboard. Use when debugging what a session actually did, step by step.
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Build a chronological, annotated event timeline for a single session.
The user provides: $ARGUMENTS
This is a session ID. It may also be:
latest / last — trace the most recently updated sessionerrors — trace the most recent session whose status is error| Endpoint | Returns |
|---|---|
GET /api/sessions?limit=N | session list (used to resolve latest/errors and the target id) |
GET /api/sessions/:id | full session detail (status, model, cwd, started_at, ended_at, cost, nested agents + events) |
GET /api/events?session_id=X | the ordered event stream: event_type, tool_name, summary, data, timestamp |
If $ARGUMENTS is a raw id, use it. If latest/last, call
GET /api/sessions?limit=1. If errors, call
GET /api/sessions?limit=10&status=error and pick the newest. Confirm the id
resolves via GET /api/sessions/:id; if not, report it as missing and stop.
From GET /api/sessions/:id: id, status, model, cwd, started_at → ended_at,
total duration, cost (USD to 4 decimals), and counts (events, agents).
From GET /api/events?session_id=X, list every event in timestamp order. One row
per event:
| # | time | Δ since prev | event_type | tool_name | summary |
Cover all event types present: SessionStart, PreToolUse, PostToolUse, Stop, SubagentStop, Compaction, APIError, TurnDuration, Notification, SessionEnd.
Annotate the timeline:
summary/data indicates
an error — mark ❌ with the error text.One line: CLEAN, GAPS DETECTED, or FAILURES PRESENT — with the count of each flag type and the single most likely thing to investigate next.
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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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