Agent skill

Audit Linearizability

by ben-manes in ben-manes/caffeine

Analyze the cache for linearizability violations across all public methods

Apache-2.0Auto-check passed

Install Audit Linearizability

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

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

GitHub CLI
$ gh skill install ben-manes/caffeine audit-linearizability --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-linearizability .claude/skills/audit-linearizability && 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-linearizability
GitHub stars
18k
Token cost
~474 tokens
SKILL.md length
216 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
Apache-2.0

At a glance

Analyze the cache for linearizability violations across all public methods

  • Works in 3 steps: State the linearization point (e.g.,… → If conditional, enumerate all cases. → Construct a 2-thread scenario confirming…
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Audit Linearizability is an agent skill from ben-manes/caffeine. Analyze the cache for linearizability violations across all public methods

Its SKILL.md is about 470 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: A high performance caching library for Java. The licence is Apache-2.0.

Example prompts

  • “/audit-linearizability”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. State the linearization point (e.g., "CAS on CHM bin at line X").
  2. If conditional, enumerate all cases.
  3. Construct a 2-thread scenario confirming the linearization point.

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

Audit Linearizability loads about 474 tokens when it runs. Until then it costs about 24 tokens; SKILL.md has 216 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~24
When it runs · the whole SKILL.md, loaded when a task matches
~474

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). 216 words, ~474 tokens.

Download SKILL.mdSave it as .claude/skills/audit-linearizability/SKILL.md (or your agent's skills folder).
name
audit-linearizability
description
Analyze the cache for linearizability violations across all public methods
context
fork
agent
auditor
disable-model-invocation
true

Analyze the cache for linearizability violations. For each public method below, identify its LINEARIZATION POINT — the single atomic step at which the operation appears to take effect.

Methods to analyze:

Single-key operations:

  • get(key), getIfPresent(key)
  • put(key, value), putIfAbsent(key, value)
  • remove(key), remove(key, value)
  • replace(key, value), replace(key, oldValue, newValue)
  • computeIfAbsent(key, function), compute(key, function), merge(key, value, function)

Bulk / aggregate operations:

  • getAll(keys) / getAllPresent(keys)
  • putAll(map)
  • invalidateAll(keys) / invalidateAll()
  • size(), containsKey(key), containsValue(value)

Note: Bulk operations are typically NOT linearizable as a unit. State whether each provides any atomicity beyond per-element linearizability.

For each method:

  1. State the linearization point (e.g., "CAS on CHM bin at line X").
  2. If conditional, enumerate all cases.
  3. Construct a 2-thread scenario confirming the linearization point.

Then attempt to construct violations: 4. Can two threads observe operations in an inconsistent order?

  • put(k, v1) / put(k, v2) / get(k): Can C see v2 then v1?
  • computeIfAbsent(k, f): Can f execute twice concurrently?
  • remove(k) / get(k): Can get return a value after remove linearized?
  1. Is size() linearizable or documented as an estimate? Bounds on error?
  2. For async cache variants: is the linearization point the future insertion or completion? Can get() return an already-replaced future?

For each candidate violation:

  • Provide the full interleaving
  • Show the sequential history it violates
  • Verify the interleaving is JMM-legal

Do not analyze internal consistency, only external observability.

© 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-linearizability of ben-manes/caffeine.

Open the folder on GitHubat commit e972fb0

Compare with similar skills

Audit Linearizability 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.

Audit Linearizability compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Audit Linearizability this skillben-manes/caffeine18k—~474Automated safety check: PassApache-2.0
Prompt Cachingsickn33/agentic-awesome-skills47k2 repos~3.4kAutomated safety check: PassMIT
Prompt Cachingdavila7/claude-code-templates33k5 repos~452Automated safety check: PassMIT
Turborepo Cachingwshobson/agents40k9 repos~2kAutomated safety check: NotesMIT
OmniRoute LLM Cachediegosouzapw/OmniRoute75k—~529Automated safety check: PassMIT
Cachingzebbern/claude-code-guide4.7k—~1.5kAutomated safety check: PassMIT

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Questions about Audit Linearizability

What does Audit Linearizability do?

Analyze the cache for linearizability violations across all public methods. Audit Linearizability is an agent skill from ben-manes/caffeine.

How do I install Audit Linearizability in Claude Code?

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

How do I install Audit Linearizability in Codex?

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

Can I use Audit Linearizability 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-linearizability -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-linearizability, .gemini/skills/audit-linearizability, .github/skills/audit-linearizability and .opencode/skills/audit-linearizability in your project.

What does Audit Linearizability need to run?

SKILL.md names no scripts, command-line tools or credentials: Audit Linearizability is instructions for the agent only.

Does Audit Linearizability 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 Audit Linearizability 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 Audit Linearizability use?

Audit Linearizability 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 Audit Linearizability use?

About 474 tokens (SKILL.md is roughly 1.9k 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 Audit Linearizability?

Skills that share tags, products or a category with Audit Linearizability: Prompt Caching (sickn33/agentic-awesome-skills, 47k stars), Prompt Caching (davila7/claude-code-templates, 33k stars), Turborepo Caching (wshobson/agents, 40k stars) and OmniRoute LLM Cache (diegosouzapw/OmniRoute, 75k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Audit Linearizability?

ben-manes (a GitHub user) maintains it in ben-manes/caffeine, which has 17,882 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 9, 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.