# token-watch

> token-watch — vedantsingh60-token-watch. Use this tool when you need to monitor and control token usage across multiple AI providers, to optimize costs and improve budget management. It analyzes token consumption patterns and provides insights to reduce expenses, making it ideal for applications with high AI usage. By tracking token metrics, it helps users make data-driven decisions to streamline their AI workflows.

Canonical page: https://skillsregistry.net/skills/vedantsingh60-token-watch  
JSON: https://api.skillsregistry.net/v1/skills/vedantsingh60-token-watch

## Description

**Track, analyze, and optimize token usage and costs across AI providers.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-05-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-09-13

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/vedantsingh60-token-watch)

## 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": "vedantsingh60-token-watch"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vedantsingh60-token-watch` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vedantsingh60-token-watch/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