# Summarization

> Use this tool when you need to condense large amounts of information quickly and efficiently, avoiding token consumption and crashes in AI projects. It solves problems related to processing extensive datasets and integrating with large language models, providing summarized output through a configurable interface using environment variables. Ideal for developers working on AI applications requiring efficient token usage, it takes in extensive data and outputs concise, summarized results.

Canonical page: https://skillsregistry.net/skills/braffolk-summarization-functions  
JSON: https://api.skillsregistry.net/v1/skills/braffolk-summarization-functions

## Description

This MCP implementation, developed by Remi Sebastian Kits, provides summarized output from various actions to avoid token consumption and crashes. It integrates with the Anthropic AI SDK and uses environment variables for configuration. Built with TypeScript and designed for Node.js 22+, it leverages modern JavaScript features and practices. The implementation is well-suited for developers working on AI projects that require efficient token usage, particularly when interfacing with large language models or processing extensive datasets. Its focus on summarization makes it valuable for applications needing to condense large amounts of information quickly and effectively.

## Trust

- **Trust score (0–1):** 0.90
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/braffolk-summarization-functions)
- **Repository:** <https://github.com/braffolk/mcp-summarization-functions>

## 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": "braffolk-summarization-functions"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/braffolk-summarization-functions` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/braffolk-summarization-functions/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