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Slash Command

Optimize Cache

Optimize caching strategies and implementation

Type
Slash Command
GitHub stars
2.8k
License
MIT
Repo last updated
Sep 27, 2026

What Optimize Cache is

Optimize Cache is a slash command published in the jeremylongshore/tons-of-skills-marketplace repository on GitHub, which has about 2.8k stars. The repository describes itself as: “Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.”

A slash command is a reusable prompt saved as a markdown file and run by typing its name after a slash. In Claude Code, custom commands have been merged into skills: a file in .claude/commands/ and a skill folder in .claude/skills/ both create the same kind of command, and existing command files keep working.

Optimize Cache gives you a repeatable way to run the same instructions without retyping them, optionally with arguments.

How to install Optimize Cache

Claude Code

  1. Download optimize-cache.md from the repository.
  2. Save it to ~/.claude/commands/ (all projects) or .claude/commands/ (one project). As a skill, you can instead save it as ~/.claude/skills/<name>/SKILL.md.
  3. Run it by typing / followed by its name.

Claude Cowork

  1. Turn the command into a skill: create a folder with the file saved as SKILL.md and zip it.
  2. In Customize → Skills, click +, then upload the ZIP.
  3. Run it from any task with / and the skill name.

New to extending Cowork? Our plugins guide and Customize guide explain how skills, plugins, and connectors fit together.

Inside the source file

An excerpt from plugins/performance/cache-performance-optimizer/commands/optimize-cache.md, shared under the repository's MIT license. Read the full file on GitHub.

Analyze and optimize caching strategies for maximum performance.

Analysis Areas

  1. Cache Hit Rates: Identify low cache hit ratios
  2. Cache Keys: Evaluate key design and granularity
  3. TTL Configuration: Time-to-live optimization
  4. Cache Invalidation: Proper invalidation strategies
  5. Cache Warming: Pre-loading critical data
  6. Cache Layers: Multi-level caching opportunities
  7. Memory Usage: Cache size and eviction policies

Process

  1. Locate all caching implementations
  2. Analyze cache usage patterns
  3. Identify cache misses and inefficiencies
  4. Evaluate TTL and invalidation strategies
  5. Generate optimization recommendations

Output

Provide report with:

  • Cache inventory and configuration analysis
  • Hit rate improvement opportunities
  • Key design recommendations
  • TTL optimization suggestions
  • Multi-level caching strategies
  • Code examples for improvements

Before you install

  • Read the whole file first. Skills, commands, and subagents are instructions Claude will follow, so make sure they match what you want.
  • Check which tools, scripts, or MCP servers it uses. Local servers and scripts run with your permissions.
  • Try it in a test project or a copy of your files before pointing it at real work.
  • Pin the version you tested, and review changes before updating.
  • Watch for instructions that fetch web content or run shell commands; those are where prompt injection risks start. See our prompt injection guide.

FAQ

What is Optimize Cache?

Optimize Cache is a slash command for Claude Code and Claude Cowork from the jeremylongshore/tons-of-skills-marketplace repository on GitHub. Optimize caching strategies and implementation

How do I install Optimize Cache in Claude Code?

Download optimize-cache.md from the repository. Save it to ~/.claude/commands/ (all projects) or .claude/commands/ (one project). As a skill, you can instead save it as ~/.claude/skills/<name>/SKILL.md. Run it by typing / followed by its name.

Can I use Optimize Cache in Claude Cowork?

Turn the command into a skill: create a folder with the file saved as SKILL.md and zip it. In Customize → Skills, click +, then upload the ZIP. Run it from any task with / and the skill name.

Is Optimize Cache safe to install?

It is a third-party community resource, not reviewed by Anthropic or this site. Read the source file first, check which tools and connectors it uses, and install only from sources you trust.

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Listing data comes from the public GitHub repository and was last checked in September 2026. Excerpts are © their authors and shared under MIT. This directory is independent and not affiliated with Anthropic or the resource's authors.