# nikhilnt

> Use this tool when you need to track and optimize LLM token costs across multiple AI models, such as Claude, GPT, and Gemini. It provides a server and CLI interface to input model usage data and outputs optimization hints and estimated cost savings. Ideal for developers and businesses looking to reduce expenses associated with large language model usage.

Canonical page: https://skillsregistry.net/skills/nikhilnt1234-tokenburnrate  
JSON: https://api.skillsregistry.net/v1/skills/nikhilnt1234-tokenburnrate

## Description

Track LLM token costs across Claude, GPT and Gemini. MCP server + CLI with optimization hints and $ savings estimates.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/w24p4s42ya)
- **Repository:** <https://github.com/nikhilnt1234/TokenBurnRate>

## 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": "nikhilnt1234-tokenburnrate"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nikhilnt1234-tokenburnrate` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nikhilnt1234-tokenburnrate/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