What is opensearch-personalize-caching-strategies?

A guide to deciding when and how to cache search results and recommendations built with AWS OpenSearch and AWS Personalize. Caching stores reusable results temporarily so they can be returned faster.

It is for designing cache keys, expiry times, user or visitor grouping, protection against traffic spikes, and monitoring for marketplace search and recommendation services.

It helps reduce repeated search and recommendation work while avoiding stale, incorrect, or overly personalised results.

opensearch-personalize-caching-strategies — Skill for Claude Code and

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 pproenca/dot-skills --skill opensearch-personalize-caching-strategies

Clone the repo

git clone --depth 1 https://github.com/pproenca/dot-skills

Made for: Claude Code, Codex.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/pproenca/dot-skills/opensearch-personalize-caching-strategies/github.svg)](https://agentmods.dev/skills/pproenca/dot-skills/opensearch-personalize-caching-strategies)

Your own site

<a href="https://agentmods.dev/skills/pproenca/dot-skills/opensearch-personalize-caching-strategies"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/opensearch-personalize-caching-strategies/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/pproenca/dot-skills/opensearch-personalize-caching-strategies"><img src="https://agentmods.dev/badge/skills/pproenca/dot-skills/opensearch-personalize-caching-strategies.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 241 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,657 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. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

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.

Model	Per session	Once invoked
Fable 5.1	$0.00241	$0.04657
Opus 5	$0.00120	$0.02329
Sonnet 5	$0.00048	$0.00931
Haiku 4.5	$0.00024	$0.00466

Measured 7d ago against content hash dfe567cb63d1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

opensearch-personalize-caching-strategies 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 7d 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/.experimental/opensearch-personalize-caching-strategies/SKILL.md · 167 lines

How it starts

The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Marketplace-Research OpenSearch + Personalize Caching Best Practices

A reference distillation of caching strategies for two-sided marketplaces running AWS OpenSearch (search) and AWS Personalize (recommendations behind a microservice). Contains 52 rules across 9 categories, ordered by cascade effect — from the upstream decision of whether to cache, through key design, personalisation boundary, strategy selection, TTL design, stampede protection, observability, and the lower-cascade categories of negative caching and tier composition. Each rule explains the WHY (the cost, latency, or correctness mechanism), shows incorrect-vs-correct code (TypeScript/Node for the microservice layer, Python for batch and analytics, OpenSearch JSON for OS-specific queries, YAML for CDN/Kubernetes), and cites the canonical source — AWS Personalize/OpenSearch/ElastiCache documentation, the XFetch paper (Vattani et al. VLDB 2015), RFC 5861 (stale-while-revalidate), and the engineering blogs of cache infrastructure teams (Netflix EVCache, Pinterest Cachelib, Twitter Twemcache, Cloudflare).

This is the complement to opensearch-function-scoring-algorithms — that skill answers "what should the ranking compute?", this skill answers "how do you scale it to production traffic without burning down OpenSearch or Personalize?"

When to Apply

Reach for this skill when:

Adding caching to a search or recommendation surface for the first time — start with decide-cache-roi-calculation and decide-hot-key-distribution
A homepage or category page renders 5+ recommenders and Personalize bills are growing faster than traffic — decide-amplification-multiplier, pers-recommender-fan-out-coalescing, pers-cohort-precomputation
Cache hit rate is suspiciously low (under 30-40%) and you don't know why — key-canonicalize-query, key-strip-volatile-params, key-bucket-numerical-ranges, obs-key-cardinality-tracking
Personalize is throttling (HTTP 429) during traffic spikes — decide-personalize-quota-budget, neg-cache-throttled-personalize, stamp-circuit-breaker-on-origin-error
p99 spikes at TTL boundaries — stamp-coalesce-concurrent-misses, stamp-probabilistic-early-expiration, stamp-serve-stale-on-rebuild, ttl-soft-and-hard, ttl-jitter-to-prevent-thundering
Recommendations stay stale after a model retrain — key-version-the-model, ttl-personalize-solution-version, strat-async-warm-up
A read-after-write surface shows stale data (user favourites, saved searches) — strat-write-through-mutations, ttl-event-driven-invalidation
Cache decisions need to be defensible to finance — decide-cache-roi-calculation, obs-cost-attribution, obs-cache-simulation-from-logs
Anonymous and logged-in traffic mix on the same routes — pers-anonymous-vs-logged-split, tier-cdn-for-anonymous
Cache is at memory pressure and you need to know whether to upsize, shorten TTL, or change strategy — decide-hot-key-distribution, tier-l2-elasticache-redis, obs-cache-simulation-from-logs
OpenSearch CPU is high on common queries — tier-opensearch-request-cache, tier-opensearch-filter-context, neg-cache-empty-results
A traffic spike from a viral link or crawler is hammering the origin — neg-bloom-filter-against-misses, neg-cache-empty-results, stamp-circuit-breaker-on-origin-error

Read the full file on GitHub · 167 lines

Files

What ships with it

56 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.

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.

7d ago First seen · 167 lines · 241 tokens per session scan A dfe567cb63d1

Subscribe to this mod's changes

opensearch-personalize-caching-strategies is a skill published in the GitHub repository pproenca/dot-skills (207 stars, last pushed 26d ago), licensed MIT. It adds 241 tokens to every session and 4,657 once invoked, about $0.0012 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 2026-09-03.

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