Agent skill

Caffeine Performance Audit

by ben-manes in ben-manes/caffeine

Audits the Caffeine cache source for hot-path costs such as allocations, contention and memory layout, reporting only findings tied to specific lines.

Apache-2.0Auto-check passedDevelopment

Install Caffeine Performance Audit

skills CLI
$ npx skills add ben-manes/caffeine --skill audit-performance -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ben-manes/caffeine audit-performance --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ben-manes/caffeine.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/audit-performance .claude/skills/audit-performance && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
audit-performance
GitHub stars
18k
Token cost
~559 tokens
SKILL.md length
229 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
Apache-2.0

At a glance

Audits the Caffeine cache source for hot-path costs such as allocations, contention and memory layout, reporting only findings tied to specific lines.

  • Works in 6 steps: Get Fast Path (highest priority) → Allocation and GC Pressure → Contention and Cache-Line Effects → …
  • Reviewing the Caffeine read path for avoidable volatile reads or allocations
  • SKILL.md covers Rules, Analysis Areas (priority order) and Output Format
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

This skill directs the agent to review the Caffeine caching library for runtime performance costs on its hot paths. It assumes the code is already heavily optimized, so generic advice is out. The agent must read the actual source, report only findings it can trace to specific lines, account for JIT optimizations such as escape analysis and inlining, and ignore correctness, style and API design.

Analysis areas are ranked. The get fast path comes first, counting volatile reads, calls, branches and allocations. Then come allocation and GC pressure, contention and cache-line effects, the FrequencySketch, worst-case maintenance work on writes, and memory layout such as node size and false sharing. Each finding lists category, location and severity, and if fewer than three real issues turn up the agent says the code is well optimized instead of padding the report.

When your agent uses it

  • Reviewing the Caffeine read path for avoidable volatile reads or allocations
  • Looking for contention or false sharing in a concurrent cache
  • Checking worst-case maintenance work and eviction cost on writes
  • Auditing JVM hot paths while ignoring optimizations the JIT already makes

Example prompts

  • “Audit the Caffeine get path and list any allocations that survive escape analysis.”
  • “Check the FrequencySketch for poor counter locality and expensive hashing.”
  • “Review the read buffer and eviction lock for contention problems.”

Requirements

  • A checkout of the Caffeine source

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Get Fast Path (highest priority)
  2. Allocation and GC Pressure
  3. Contention and Cache-Line Effects
  4. FrequencySketch
  5. Maintenance Work
  6. Memory Layout

What it can do on your machine

Read from SKILL.md and the folder at commit e972fb0. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Caffeine Performance Audit loads about 559 tokens when it runs. Until then it costs about 25 tokens; SKILL.md has 229 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~25
When it runs · the whole SKILL.md, loaded when a task matches
~559

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ben-manes/caffeine at commit e972fb0, republished under its Apache-2.0 licence (© ben-manes). 229 words, ~559 tokens.

Download SKILL.mdSave it as .claude/skills/audit-performance/SKILL.md (or your agent's skills folder).
name
audit-performance
description
Audit hot paths for performance inefficiencies (allocations, contention, layout)
context
fork
agent
auditor
disable-model-invocation
true

Audit the Caffeine cache for performance inefficiencies.

Context: Caffeine runs in high-throughput, low-latency JVM services where cache operations occur millions of times per second. The library is already heavily optimized — generic textbook advice is not useful.

Rules

  1. Read the actual source code before analyzing.
  2. Only report findings traceable to specific lines.
  3. Account for JIT compilation. C2 eliminates many apparent inefficiencies: escape analysis, inlining, dead code elimination. Don't flag JIT-optimized issues.
  4. Ignore correctness, style, and API design. This is purely runtime performance.
  5. Quality over quantity. Five real findings beat twenty speculative ones.

Analysis Areas (priority order)

1. Get Fast Path (highest priority)

Trace get()/getIfPresent() from entry to return. Count volatile/opaque reads, method calls, branches, allocations. Even one saved volatile read matters.

2. Allocation and GC Pressure

Identify allocations surviving escape analysis on hot paths. Frequency, size, lifetime. Do not flag JIT-eliminated allocations.

3. Contention and Cache-Line Effects

CAS retry rates, cache-line bouncing, graceful vs catastrophic degradation for read buffer, evictionLock, CHM bins, node field updates.

4. FrequencySketch

Counter layout locality, hash computation, reset cost. Accessed every read/write.

5. Maintenance Work

Worst-case work per write, latency spikes, eviction cascades, timer wheel scan cost.

6. Memory Layout

Node object size, pointer indirection depth, false sharing, @Contended opportunities.

Output Format

For each finding:

## [Category] Title
**Location:** file:method (lines X-Y)
**Severity:** negligible | moderate | high
**What happens:** (trace the code path)
**Why it matters:** (quantify)
**JIT considerations:** (will C2 handle this?)
**Proposed fix:** (specific code change)
**Expected benchmark impact:** (JMH prediction)

If fewer than 3 real issues, the code is well-optimized. Do not pad the output.

© ben-manes, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/audit-performance of ben-manes/caffeine.

Open the folder on GitHubat commit e972fb0

Compare with similar skills

Caffeine Performance Audit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Caffeine Performance Audit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Caffeine Performance Audit this skillben-manes/caffeine18k—~559Automated safety check: PassApache-2.0
Code Review Skillawesome-skills/code-review-skill2.1k—~2.8kAutomated safety check: NotesMIT
Coding Standardsapache/shardingsphere21k—~2.2kAutomated safety check: PassApache-2.0
Code Review Specialistluongnv89/claude-howto42k—~764Automated safety check: PassMIT
New Rule for sonar-javaSonarSource/sonar-java1.2k—~833Automated safety check: PassCustom licence
Cross-Language Coding Standardszereight/gitlab-mcp2k1 repos~1.4kAutomated safety check: PassMIT

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More from ben-manes/caffeine

All 33 skills in this repo
  • Runs controlled JMH experiments on the Caffeine cache to find shared contention and hot-path waste, then reviews correctness and returns a reviewable patch.

    18k GitHub stars~2.6k tokensUpdated 2 days ago
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  • Git History Bug Audit

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  • Adversarial Codebase Audit

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  • Audit Sibling Divergence

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    Compares code paths that should behave the same, such as sync and async cache methods, and requires a concrete scenario where the two observably disagree.

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  • Climber Step Minimization

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    Prices each step of the window climber algorithm by disabling it in turn, to find steps that no longer earn their keep and branches that no longer fire.

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Works with

Categories

Questions about Caffeine Performance Audit

What does Caffeine Performance Audit do?

Audits the Caffeine cache source for hot-path costs such as allocations, contention and memory layout, reporting only findings tied to specific lines. This skill directs the agent to review the Caffeine caching library for runtime performance costs on its hot paths. It assumes the code is already heavily optimized, so generic advice is out.

When should I use Caffeine Performance Audit?

Caffeine Performance Audit fits situations like: reviewing the Caffeine read path for avoidable volatile reads or allocations; looking for contention or false sharing in a concurrent cache; checking worst-case maintenance work and eviction cost on writes; auditing JVM hot paths while ignoring optimizations the JIT already makes.

How do I install Caffeine Performance Audit in Claude Code?

Run `npx skills add ben-manes/caffeine --skill audit-performance -a claude-code`. Or copy the skill folder (.claude/skills/audit-performance in ben-manes/caffeine) into .claude/skills/audit-performance in your project. Claude Code loads it when a task matches its description.

How do I install Caffeine Performance Audit in Codex?

Run `npx skills add ben-manes/caffeine --skill audit-performance -a codex`. Or copy the skill folder (.claude/skills/audit-performance in ben-manes/caffeine) into .agents/skills/audit-performance in your project. Codex loads it when a task matches its description.

Can I use Caffeine Performance Audit in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ben-manes/caffeine --skill audit-performance -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/audit-performance, .gemini/skills/audit-performance, .github/skills/audit-performance and .opencode/skills/audit-performance in your project.

What does Caffeine Performance Audit need to run?

SKILL.md names no scripts, command-line tools or credentials: Caffeine Performance Audit is instructions for the agent only. Our summary lists: A checkout of the Caffeine source.

Does Caffeine Performance Audit access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Caffeine Performance Audit safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Caffeine Performance Audit use?

Caffeine Performance Audit is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Caffeine Performance Audit use?

About 559 tokens (SKILL.md is roughly 2.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Caffeine Performance Audit?

Skills that share tags, products or a category with Caffeine Performance Audit: Code Review Skill (awesome-skills/code-review-skill, 2.1k stars), Coding Standards (apache/shardingsphere, 21k stars), Code Review Specialist (luongnv89/claude-howto, 42k stars) and New Rule for sonar-java (SonarSource/sonar-java, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Caffeine Performance Audit?

ben-manes (a GitHub user) maintains it in ben-manes/caffeine, which has 17,880 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 6, 2026.

Source: ben-manes/caffeine on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.