Run a daily spend check-in against a daily budget on the Agent Monitor dashboard — today's spend vs the daily target, pace through the day, and the projected overage if the current pace holds. Uses /api/pricing/cost and /api/sessions (grouped by started_at = today). Use for a quick daily spend check-in or a morning/evening budget pulse.
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A fast daily pulse: are you on pace against today's budget?
The user provides: $ARGUMENTS
This is the daily budget in dollars — e.g. "5" or "$5/day". If omitted, ask
for one or derive it from a monthly budget (monthly / days_in_month) and state the
assumption.
| Endpoint | Returns |
|---|---|
GET /api/pricing/cost | { total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] } — fleet-wide spend and the avg cost-per-session used to value today's sessions |
GET /api/sessions?limit=200 | Session list with inline cost and started_at — filter to today (DATE(started_at) = today) to isolate today's spend |
Spend has no per-day field, so isolate today from the session list:
started_at is today (local date).cost over today's sessions. If inline cost is absent for some rows, fall back to today_session_count × (total_cost / total_session_count) and flag it as approximate.fraction_of_day_elapsed = hours_since_midnight / 24. expected_by_now = daily_budget × fraction_of_day_elapsed.today_spend − expected_by_now (▲ ahead of budget / ▼ behind).projected_today = today_spend / fraction_of_day_elapsed (linear extrapolation of the current pace). Guard against tiny fraction_of_day_elapsed early in the day — if under ~0.1, label the projection low-confidence.projected_today − daily_budget (positive = over).One headline line: today's spend / daily budget, and the percent consumed. Verdict: under / on pace / over.
expected_by_now vs actual today_spend, the ▲/▼ pace delta, and the fraction of the day elapsed.
projected_today and the projected overage/headroom vs the daily budget. Note the confidence (low early in the day).
Today's sessions ranked by cost (top 5): name/id, model, cost. Surface any premium-model session inflating the day.
If projected over: one concrete cut (route the priciest session type cheaper — see model-savings; or arm a token_threshold rule via budget-set). If under: confirm headroom and the remaining daily allowance.
Compact Markdown — this is a daily check-in, keep it tight. Currency as USD to 4 decimal places; pace deltas with ▲/▼. Lead with the verdict line.
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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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