cache-recon

cache-recon is a skill for Claude Code from tonone-ai/tonone. It costs 45 tokens per session (372 once invoked), scanned A, original, MIT.

A review of an existing application cache, including its settings, key patterns, and caching code. It looks for missing expiry times, collisions, low hit rates, and request surges called cache stampedes.

In plain words
What is it for?
Use it to audit Redis or Memcached setups, investigate low hit rates, find stampede risks, and recommend fixes.
Why use it?
It helps explain why a cache is missing often or serving risky data, and identifies design problems before they affect reliability.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool; mentions Claude Code.

Part of the tonone plugin — 41 skills, 100 agents, 8 plugins shipped together

Good fit Use it to audit Redis or Memcached setups, investigate low hit rates, find stampede risks, and recommend fixes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tonone-ai/tonone/cache-recon
Install

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.

Any agent
npx skills add tonone-ai/tonone --skill cache-recon
Clone the repo
git clone --depth 1 https://github.com/tonone-ai/tonone

Made for: Claude Code.

Or install tonone, the plugin that ships this one along with the rest of its 41 skills, 100 agents, 8 plugins.

Wrote 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.

agentmods badge for cache-recon

README.md
[![agentmods](https://agentmods.dev/badge/skills/tonone-ai/tonone/cache-recon/github.svg)](https://agentmods.dev/skills/tonone-ai/tonone/cache-recon)
Your own site
<a href="https://agentmods.dev/skills/tonone-ai/tonone/cache-recon"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/cache-recon/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.

agentmods 80×15 button for cache-recon

Your own site · 80×15
<a href="https://agentmods.dev/skills/tonone-ai/tonone/cache-recon"><img src="https://agentmods.dev/badge/skills/tonone-ai/tonone/cache-recon.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 372 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.00372
Opus 5.5 $0.00018 $0.00149
Sonnet 5.5 $0.00009 $0.00074
Haiku 4.5 $0.00005 $0.00037

Measured 1mo ago against content hash 2cff87927f61, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

cache-recon 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 1mo 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.

skills/cache-recon/SKILL.md · 47 lines

What it actually says

Cache Recon

You are Cache — Caching Strategy Engineer on the Infrastructure Specialist Team.

Steps

Step 0: Confirm Context

Ask the user for any missing context needed to produce a useful output. If the request is clear, skip questions and proceed.

Step 1: Gather Context

Read existing Redis/Memcached config, cache key patterns, and application caching code. Check for missing TTLs, thundering herd risks, and key collisions.

Step 2: Produce Output

Report: missing TTLs, key design issues, stampede risks, eviction policy mismatches, and recommended improvements.

Step 3: Summary

Output a brief summary:

  • What was produced
  • Key risks or tradeoffs
  • Recommended next steps

Key Rules

  • Follow the output format defined in docs/output-kit.md
  • Always quantify tradeoffs: cost, reliability, and operational complexity
  • Flag when recommendation requires production validation or load testing

Delivery

If output exceeds the 40-line CLI budget, invoke /atlas-report with the full findings. The HTML report is the output. CLI is the receipt — box header, one-line verdict, top 3 findings, and the report path. Never dump analysis to CLI.

Changes

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.

  1. 1mo ago First seen · 47 lines · 45 tokens per session scan A 2cff87927f61

Subscribe to this mod's changes

cache-recon is a skill published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 10d ago), licensed MIT. It adds 45 tokens to every session and 372 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-20.

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