Suggest concrete optimizations for Claude Code usage based on historical session data. Covers cost reduction, speed improvement, error prevention, and workflow efficiency. Use for data-driven optimization planning.
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Generate data-driven optimization recommendations for Claude Code usage.
The user provides: $ARGUMENTS
This may be:
Gather optimization data from http://localhost:4820:
GET /api/sessions?limit=200 — session historyGET /api/analytics — tool and token analyticsGET /api/pricing/cost — cost dataGET /api/pricing — pricing rules for model comparisonAnalyze optimization opportunities:
Quantify each recommendation:
Present as a prioritized optimization plan:
| # | Recommendation | Category | Impact | Effort | Priority |
|---|---|---|---|---|---|
| 1 | Specific action | 💰/⚡/🛡/🔄 | High | Low | ★★★★★ |
| 2 | Specific action | ... | ... | ... | ★★★★☆ |
For the top 5 recommendations, include:
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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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