Individual skill
cache-efficiency
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.
plugins/ccam-analytics/skills/cache-efficiency/SKILL.md
Source commit 14907bd6420bae80ddc01d0b7cd657980f0cf2d0
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- Last checked
- Nov 11, 2026
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- Repository last updated
- Nov 8, 2026
- License
- MIT
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SKILL.mdcore · 3,881 bytesagents/openai.yamlasset · 269 bytes
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# 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 |
|----------|---------|