audit-prompt-caching
audit-prompt-caching is an LLM evaluation & observability skill for AI agents, published by sernote in the audit-prompt-caching repository on GitHub. Skillspace rates audit-prompt-caching D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Use whenever the user mentions LLM prompt/prefix cache misses, cached_tokens=0, cache_read_input_tokens/cache_creation_input_tokens, prompt_cache_key, cache_control/cachePoint, TTFT/prefill latency, KV reuse, LLM cost or speed regressed on repeated long prompts, or speeding up agents through cache stability. Use for LLM request shape changes: prompt text/order/builders, tools, schemas, response_format, model/router, agent loops, or compaction. Not for generic prompt writing/RAG, token counts, or non-LLM perf.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 97
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 81 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- Low-risk patterns
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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