# token-optimizer

> Use this tool when you need to reduce Large Language Model (LLM) API costs without modifying code. The token-optimizer achieves this through semantic caching, prompt compression, model routing, and context pruning, making it a valuable solution for cost optimization and efficient LLM usage. Ideal for applications with high LLM API usage, it streamlines processes and minimizes expenses.

Canonical page: https://skillsregistry.net/skills/prompt-thin-token-optimizer  
JSON: https://api.skillsregistry.net/v1/skills/prompt-thin-token-optimizer

## Description

Reduce LLM API costs via semantic caching, prompt compression, model routing and context pruning. Zero code changes required.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-05-13

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/prompt_thin/token-optimizer)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "prompt-thin-token-optimizer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/prompt-thin-token-optimizer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/prompt-thin-token-optimizer/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt