About this project

slim-down is a personal project by a single developer, built to solve a concrete problem: documents and data are rarely already in the shape an AI model actually needs.

Why slim-down exists

Word documents, PowerPoint presentations, and HTML pages carry formatting, styling, and metadata that add no meaning for a language model, but do cost tokens. Converting content to clean Markdown first keeps the structure (headings, tables, lists) intact while often cutting token usage substantially.

Who's behind it

slim-down is built and maintained by a single independent developer, as a personal project with no company or business registration behind it. Questions or feedback reach the administrator directly via the contact page.

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🔑 REST API Access & Keys

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Securely sync documents across all your devices.

⚡ REST API Endpoints

POST /api/convert

Tekst, CSV, JSON, HTML, YAML

Converts input to Markdown or another target format. Optionally add save: true to automatically save the result to your account.

curl -X POST https://slim-down.nl/api/convert \
  -H "Authorization: Bearer <JOUW_API_SLEUTEL>" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "Product,Prijs\nLaptop,999",
    "source_format": "csv",
    "target_format": "markdown"
  }'

POST /api/convert-file

.pdf, .docx, .doc, .pptx, .ppt, .xlsx, .xls, .ipynb

Upload PDF, Word, PowerPoint, Excel, or Jupyter Notebook files via multipart form-data for direct conversion to Markdown or CSV.

curl -X POST https://slim-down.nl/api/convert-file \
  -H "X-API-Key: <JOUW_API_SLEUTEL>" \
  -F "file=@document.docx"

GET /api/documents

Cloud Sync

Retrieves all your saved documents in JSON format for sync across apps and devices.

curl -X GET https://slim-down.nl/api/documents \
  -H "Authorization: Bearer <JOUW_API_SLEUTEL>"

GET /api/auth/me

User Info & Token Validation

Checks if your API key is valid and returns user profile information.

curl -X GET https://slim-down.nl/api/auth/me \
  -H "Authorization: Bearer <JOUW_API_SLEUTEL>"

🤖 AI Integrations & Token Reduction Examples

Claude • Gemini • Copilot

Convert documents or raw data via slim-down to compact Markdown before sending them as context to an LLM to save tokens and costs.

⚡ Claude Tool / Skill (Function Calling) (Anthropic Tool Use schema & Python handler)

Give Claude the skill/tool to automatically call the slim-down API when it needs to simplify a document, table, or JSON/HTML:

import requests
from anthropic import Anthropic

SLIM_DOWN_KEY = "JOUW_SLIM_DOWN_API_SLEUTEL"
SLIM_DOWN_URL = "https://slim-down.nl/api/convert"

# 1. Definieer de slim-down Skill / Tool voor Claude
tools = [
    {
        "name": "slim_down_convert",
        "description": "Converteert HTML, JSON, YAML, CSV, Word of platte tekst naar compacte Markdown om tokens te besparen.",
        "input_schema": {
            "type": "object",
            "properties": {
                "content": {
                    "type": "string",
                    "description": "De ruwe tekst, html, json, yaml of csv content"
                },
                "target_format": {
                    "type": "string",
                    "enum": ["markdown", "json", "yaml", "csv", "excel", "text"],
                    "default": "markdown"
                }
            },
            "required": ["content"]
        }
    }
]

# 2. Tool handler functie
def run_slim_down_tool(content: str, target_format: str = "markdown") -> str:
    resp = requests.post(
        SLIM_DOWN_URL,
        headers={"Authorization": f"Bearer {SLIM_DOWN_KEY}"},
        json={"input": content, "target_format": target_format}
    )
    return resp.json().get("result", "")

# 3. Claude aanroepen met de tool
client = Anthropic()
response = client.messages.create(
    model="claude-3-7-sonnet-20250219",
    max_tokens=1024,
    tools=tools,
    messages=[
        {
            "role": "user",
            "content": "Kun je deze HTML tabel versimpelen naar Markdown?\n<table><tr><th>Naam</th><th>Score</th></tr><tr><td>Alex</td><td>95</td></tr></table>"
        }
    ]
)
print("Tool calls:", response.content)

💬 System Prompts & AI Instructions (Claude Projects, Custom GPTs & Cursor rules)

Use this prompt in your Claude Project Custom Instructions, System Prompt, or .cursorrules:

### SYSTEM PROMPT / AI INSTRUCTION:
You have access to the slim-down conversion API at https://slim-down.nl.
When the user asks to analyze large HTML pages, Word files (.docx), Excel sheets (.xlsx), JSON data, or CSV:
1. Use the slim-down API endpoint (POST /api/convert or POST /api/convert-file)
   with header "Authorization: Bearer <YOUR_SLIM_DOWN_KEY>".
2. Always convert the input to "markdown" first to minimize token consumption.
3. Answer the user's question solely based on the resulting clean Markdown.

🟣 Anthropic Claude (Direct SDK) (Python Anthropic SDK + Document Context)

First upload your Word/Excel/JSON file to slim-down and send the clean Markdown context directly to Claude 3.5 / 3.7:

import requests
from anthropic import Anthropic

SLIM_DOWN_KEY = "JOUW_SLIM_DOWN_API_SLEUTEL"
CLAUDE_KEY = "sk-ant-..."

# 1. Converteer Word/Excel naar compacte Markdown via slim-down
with open("jaarverslag.docx", "rb") as f:
    res = requests.post(
        "https://slim-down.nl/api/convert-file",
        headers={"X-API-Key": SLIM_DOWN_KEY},
        files={"file": f}
    )
clean_markdown = res.json()["result"]

# 2. Stuur de geoptimaliseerde context naar Claude
client = Anthropic(api_key=CLAUDE_KEY)
message = client.messages.create(
    model="claude-3-7-sonnet-20250219",
    max_tokens=1000,
    messages=[
        {
            "role": "user",
            "content": f"Analyseer dit document en geef de 3 belangrijkste KPI's:\n\n{clean_markdown}"
        }
    ]
)
print(message.content[0].text)

🔵 Google Gemini (Python google-genai / google-generativeai SDK)

Optimize spreadsheets or raw tables into Markdown tables for Gemini 2.0 / 1.5 Flash:

import requests
import google.generativeai as genai

SLIM_DOWN_KEY = "JOUW_SLIM_DOWN_API_SLEUTEL"
genai.configure(api_key="AIzaSy...")

# 1. Converteer complexe spreadsheet of CSV data naar Markdown tabel
raw_csv = (
    "Afdeling,Q1,Q2,Budget\n"
    "Sales,120000,145000,250000\n"
    "Marketing,45000,60000,100000"
)
conv = requests.post(
    "https://slim-down.nl/api/convert",
    headers={"Authorization": f"Bearer {SLIM_DOWN_KEY}"},
    json={"input": raw_csv, "source_format": "csv", "target_format": "markdown"}
).json()

# 2. Vraag Gemini om samenvatting met minimale tokens
model = genai.GenerativeModel("gemini-2.0-flash")
response = model.generate_content(
    f"Hier zijn de kwartaalcijfers in Markdown:\n\n{conv['result']}\n\nWelke afdeling benadert zijn budget?"
)
print(response.text)

🤖 GitHub Copilot, Cursor & ChatGPT (Prompt Engineering & Context Injection)

Copy the converted Markdown directly into your IDE or Copilot Chat window with the following structured prompt template:

You are an AI assistant. Use the specification below (converted via slim-down)
as the source of truth for the implementation.

### SOURCE DOCUMENT (Markdown):
{{PASTE CONVERTED SLIM-DOWN OUTPUT HERE}}

### INSTRUCTIONS:
Write the required Go / TypeScript dataclasses and validation rules based on the tables above.

🐍 🟨 Python & JavaScript Integration Examples

Python (requests)

import requests

headers = {
    "Authorization": "Bearer JOUW_API_SLEUTEL",
    "Content-Type": "application/json"
}
payload = {
    "input": "# Titel\nInhoud converteren",
    "target_format": "html"
}
res = requests.post("https://slim-down.nl/api/convert", json=payload, headers=headers)
print(res.json()["result"])

JavaScript / Node.js (fetch)

const res = await fetch("https://slim-down.nl/api/convert", {
  method: "POST",
  headers: {
    "Authorization": "Bearer JOUW_API_SLEUTEL",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    input: "Product,Prijs\nBoek,15.00",
    target_format: "markdown"
  })
});
const data = await res.json();
console.log(data.result);