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 agentmods add skills/codebygarv/ai-skills/cache-strategy-plannernpx skills add codebygarv/Ai-skills --skill cache-strategy-plannergit clone --depth 1 https://github.com/codebygarv/Ai-skillsWrote 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/codebygarv/ai-skills/cache-strategy-planner)<a href="https://agentmods.dev/skills/codebygarv/ai-skills/cache-strategy-planner"><img src="https://agentmods.dev/badge/skills/codebygarv/ai-skills/cache-strategy-planner.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00030 | $0.00392 |
| Opus 5 | $0.00015 | $0.00196 |
| Sonnet 5 | $0.00006 | $0.00078 |
| Haiku 4.5 | $0.00003 | $0.00039 |
Grade A, and why
cache-strategy-planner 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 4d 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.
What it actually says
Purpose
Architect robust, multi-layer caching strategies (HTTP/CDN edge, distributed Redis/Memcached, in-process local memory) with explicit TTLs, cache invalidation hooks, and cache stampede (thundering herd) protections.
When to Use
- High-read database bottlenecks or slow third-party API response times.
- Designing CDN caching rules (
Cache-Control,stale-while-revalidate, surrogate keys). - Fixing cache stampedes that crash origin servers when popular cache keys expire.
What to Analyze
- Cache Tier Selection: L1 (In-memory LRU, sub-millisecond) vs L2 (Redis Cluster, 1-2ms) vs Edge CDN (Cloudflare/Fastly).
- Write Strategy: Cache-Aside (Lazy Loading), Write-Through, Write-Behind (Write-Back).
- Invalidation Policy: Time-To-Live (TTL) with jitter vs Event-driven explicit key purge vs Tag-based invalidation.
- Stampede & Thundering Herd Defense: Mutex locking (singleflight pattern) or probabilistic early expiration (XFetch algorithm).
- Serialization & Memory Footprint: Protobuf, MessagePack, or compressed JSON over raw strings.
Output Format
- Caching Architecture Diagram: Data flow between Client, CDN, Redis, and Database.
- Cache Policy Table: [Data Type | Storage Tier | TTL | Invalidation Trigger | Stampede Defense].
- Singleflight / Cache Wrapper Code: Production-ready caching utility with fallback.
Avoid
- Caching mutable data without a clear invalidation strategy.
- Omitting TTL jitter (all cache keys expiring at the exact same second).
What ships with it
2 files 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.
- 4d ago First seen · 34 lines · 30 tokens per session scan A 12ef12a6a4c4
cache-strategy-planner is a skill published in the GitHub repository codebygarv/Ai-skills (24 stars, last pushed 15d ago), licensed MIT. It adds 30 tokens to every session and 392 once invoked, about $0.0002 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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