# spendwatch

> spendwatch — cognis-digital-spendwatch. Use this tool when you need to monitor and manage Large Language Model (LLM) usage across multiple providers, tracking costs and rate limits while setting budget guards. It supports various providers, including Anthropic, OpenAI, and OpenRouter, with a text-based user interface and integration with git. Ideal for developers and teams looking to optimize LLM usage and prevent unexpected expenses.

Canonical page: https://skillsregistry.net/skills/cognis-digital-spendwatch  
JSON: https://api.skillsregistry.net/v1/skills/cognis-digital-spendwatch

## Description

Multi-provider LLM usage, cost & rate-limit meter with budget guards — Anthropic/OpenAI/OpenRouter/local, TUI + MCP + CI exit codes. Zero-dependency.

## Trust

- **Trust score (0–1):** 0.63
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/cognis-digital/spendwatch)

## 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": "cognis-digital-spendwatch"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cognis-digital-spendwatch` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cognis-digital-spendwatch/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