Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add hoangsonww/Claude-Code-Agent-Monitor --skill cache-efficiencygit clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-MonitorWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/cache-efficiency)<a href="https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/cache-efficiency"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/cache-efficiency/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hoangsonww/claude-code-agent-monitor/cache-efficiency"><img src="https://agentmods.dev/badge/skills/hoangsonww/claude-code-agent-monitor/cache-efficiency.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00100 | $0.00933 |
| Opus 5 | $0.00050 | $0.00466 |
| Sonnet 5 | $0.00020 | $0.00187 |
| Haiku 4.5 | $0.00010 | $0.00093 |
Grade A, and why
cache-efficiency scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
From /api/analytics: compute cache_hit_rate × 100. State raw total_cache_read and total_input. Benchmark: >70% strong, 40–70% moderate, <40% weak prompt-cache utilization.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 67 lines · 100 tokens per session scan A 6082e3cddc82
cache-efficiency is a skill published in the GitHub repository hoangsonww/Claude-Code-Agent-Monitor (989 stars, last pushed 2d ago), licensed MIT. It adds 100 tokens to every session and 933 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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