# cache-efficiency

The skill works out whether prompt caching pays off: hit rate, write-versus-read reuse, and what each side costs in dollars.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · ★ 1114
- Author: hoangsonww
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/HEAD/plugins/ccam-analytics/skills/cache-efficiency/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/cache-efficiency

## What it does

It reads from the Agent Monitor dashboard. Token totals come from `/api/analytics`, per-session rows from `/api/sessions`, and money from `/api/pricing/cost`. You get a Markdown report with tables: the hit rate, how many tokens were written against how many were read, and the dollar split between the two. One section ranks the ten sessions with the weakest reuse.

The math is short. `cache_hit_rate = total_cache_read / (total_cache_read + total_input)`, and `cache_reuse = total_cache_read / total_cache_write`. A reuse figure below 1 means you are paying to cache context you hardly read back. Cache writes cost more per token than reads, and they are billed even when the cached block never gets reused. Counts are effective totals, `current + baseline`, so pre-compaction tokens stay in the picture.

The skill takes an argument: leave it empty to cover everything, pass a window such as “today”, a session ID to narrow the scope, or a target like “hit rate > 80%”. Without Agent Monitor running, there is nothing to pull — all four endpoints belong to that dashboard.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill cache-efficiency -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/cache-efficiency/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/cache-efficiency/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill cache-efficiency -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/cache-efficiency/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill cache-efficiency -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/cache-efficiency/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install hoangsonww/Claude-Code-Agent-Monitor cache-efficiency
```

2. **Manually: put the files in place**
- File: `.github/skills/cache-efficiency/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill cache-efficiency -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/hoangsonww/Claude-Code-Agent-Monitor --path plugins/ccam-analytics/skills/cache-efficiency
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/cache-efficiency/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill cache-efficiency -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/HEAD/plugins/ccam-analytics/skills/cache-efficiency/SKILL.md

## When to use it
- measure the prompt cache hit rate across all sessions
- spot sessions that write far more cache than they read
- split cache spend into read and write dollars
- estimate the savings from a higher hit rate
- drill into one session with poor reuse

## Example prompts
- Analyze prompt cache efficiency for this week
- Show the sessions with the worst cache reuse
- Drill into session `abc123` — why is its cache read so low?

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: b20ddd2d4635b067.

BEGIN THIRD-PARTY FILE b20ddd2d4635b067
````text
---
name: cache-efficiency
description: >
  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.
---

# 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 if the cached block is never reused. The payoff only arrives on subsequent reads — so a healthy fleet shows **cache_read_tokens far exceeding cache_write_tokens**. When `cache_reuse < 1`, you are paying to cache context you barely re-read.

Token counts are **effective totals** = `current + baseline` (baselines preserve pre-compaction tokens).

## Report Sections

### 1. Fleet Cache Hit Rate
````
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First 2436 of 3881 bytes. © hoangsonww · MIT · https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/HEAD/plugins/ccam-analytics/skills/cache-efficiency/SKILL.md

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---
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