prompt-caching
Optimize LLM Prompt Caching
Repeated prompts can increase latency and LLM spend. This skill helps teams choose prompt, response, and CAG caching patterns.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "prompt-caching" from https://skillstore.io/skills/sickn33-prompt-caching.md and its manifest at https://skillstore.io/api/skills/sickn33-prompt-caching/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "prompt-caching". A support chatbot repeats a long policy manual in every request.
Expected outcome:
Use prefix caching for stable policy text. Keep volatile user details later in the prompt to protect cache hits.
Using "prompt-caching". A summarization service uses high temperature and caches full responses.
Expected outcome:
Avoid full response caching for this path. Lower temperature or cache only deterministic stages with clear freshness rules.
Using "prompt-caching". A team wants to preload stable documentation instead of retrieving it each turn.
Expected outcome:
Consider CAG when documents are small enough, stable, and reused often. Add invalidation when the documentation changes.
Security Audit
SafeThe only static finding is a false positive caused by Markdown inline code in SKILL.md. I found no evidence of command execution, prompt injection, data exfiltration, or malicious intent in the reviewed file.
Risk Factors
⚙️ External commands (1)
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APA citation
sickn33. (2026). prompt-caching security audit report (audit version 4) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-prompt-caching/audits/4BibTeX citation
@techreport{sickn33-sickn33-prompt-caching-2026,
author = {sickn33},
title = {prompt-caching security audit report (audit version 4)},
institution = {Skillstore},
year = {2026},
number = {4},
url = {https://skillstore.io/skills/sickn33-prompt-caching/audits/4},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "prompt-caching security audit report (audit version 4)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-07"
url: "https://skillstore.io/skills/sickn33-prompt-caching/audits/4"
identifiers:
- type: other
value: "skillstore:sickn33-prompt-caching:audit:4"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Reduce Repeated Prompt Cost
Plan prefix caching for shared instructions, tool schemas, and documents that repeat across calls.
Design Response Cache Rules
Define cache keys, freshness rules, and invalidation paths for repeated user requests.
Evaluate CAG Versus RAG
Compare preloaded document context with retrieval when documents are stable and frequently reused.
Try These Prompts
Explain the differences between prefix caching, response caching, and CAG for my application. Recommend the safest first step.
Review this prompt structure: [paste structure]. Identify stable prefixes, cache boundaries, and changes that reduce cache misses.
Create a response caching policy for my workflow. Include cache keys, temperature limits, invalidation triggers, and monitoring signals.
Audit this LLM caching design: [describe architecture]. Find risks across prefix, response, semantic, and CAG layers, then propose improvements.
Best Practices
- Keep stable instructions and documents at the beginning of prompts.
- Cache deterministic or low-temperature responses with explicit freshness rules.
- Measure hit rate, miss latency, stale responses, and cost before expanding scope.
Avoid
- Caching high-temperature creative outputs as if they were deterministic.
- Changing prompt prefixes on every request and expecting provider cache hits.
- Caching sensitive or fast-changing data without expiration and invalidation.