cache-efficiency

# Cache Efficiency Diagnose whether prompt caching is actually saving money, and where it is not. ## Input The user provides: **$ARGUMENTS** This may be: empty (analyze the whole fleet), "today" / "this week" / a date range, a session ID to scope the analysis, or a target like "hit rate > 80%". When empty, analyze all data from `/api/analytics`. ## Data Sources | Endpoint | Returns | |----------|---------| | `GET /api/analytics` | `tokens.total_input`, `tokens.total_output`, `tokens.total_cache_read`, `tokens.total_cache_write` (baselines pre-summed), plus `daily_sessions` | | `GET /api/sessions?limit=200` | Session list — each has model, cwd, started_at, ended_at, inline `cost`, metadata (JSON: usage_extras with cache token detail) | | `GET /api/sessions/{id}` | Full session detail with nested agents and events, for drill-down on a flagged session | | `GET /api/pricing/cost` | `{ total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] }` — used to price cache read vs write spend | ### How cache economics work ``` cache_hit_rate = total_cache_read / (total_cache_read + total_input) cache_reuse = total_cache_read / total_cache_write cache_read_cost = (cache_read_tokens / 1M) × cache_read_per_mtok cache_write_cost = (cache_write_tokens / 1M) × cache_write_per_mtok ``` Cache writes cost more per token than cache reads (e.g. Sonnet $3.75 write vs $0.30 read per Mtok), and writes are billed even i...