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Text Summarizer (TLDR / Bullets / Paragraph / Executive Summary)
x402
Text Summarizer (TLDR / Bullets / Paragraph / Executive Summary) is a paid API for AI agents from x402-deployer.x402-deployer.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-14).
Summarizes up to 30,000 characters of input text into TLDR, bullet points, paragraph, or executive summary format using Mistral AI, with adjustable length, tone, and structure.
Price / call$0.01
Success—
StatusUnknown
How this service works
Summarize text into TLDR, bullets, paragraph, or executive summary. Up to 30k chars input. Mistral-powered. Adjustable length, tone, and structure.
Output
Returns a condensed version of the input text in the requested format (TLDR, bullets, paragraph, or executive summary), adjusted for the specified length and tone.
Example use cases
Example prompt
“Can you summarize the following 10,000-character article into bullet points with a professional tone and keep it medium length? Here's the text: [article text]”
Technical details
Endpoint
POSThttps://x402-deployer.x402-deployer.workers.dev/summarize-textWhen to prefer
Use this endpoint when you need to programmatically summarize long-form text content (up to 30k chars) and want flexible output formats (TLDR, bullets, paragraph, or executive summary) with control over tone and length. Prefer this over general LLM calls when you want a pay-per-use, specialized summarization endpoint without managing your own Mistral API key.
Side effects
- Input text exceeds 30,000 character limit — returns error
- Unsupported summary format specified — returns validation error
- Empty or too-short input text — returns error or minimal summary
- Mistral API timeout or unavailability — returns upstream error
- Payment not processed — returns 402 Payment Required
Input
{
"input": {
"body": {
"text": "Artificial intelligence has revolutionized many industries over the past decade. Machine learning algorithms now power recommendation systems, autonomous vehicles, and medical diagnostic tools. Natural language processing enables chatbots and translation services. Computer vision applications range from facial recognition to agricultural monitoring. Despite these advances, challenges remain in areas like bias mitigation, interpretability, and energy efficiency. Researchers continue to explore novel architectures and training methods to improve AI capabilities while addressing ethical concerns. The future of AI likely involves more specialized models, better integration with domain expertise, and stronger focus on responsible development practices.",
"style": "bullets",
"max_words": 100
},
"type": "http",
"method": "POST",
"bodyType": "json"
}
}Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
{
"model": "hermes-3-llama-3.1-405b",
"style": "bullets",
"source": "morpheus",
"summary": "- AI has transformed industries through machine learning, natural language processing, and computer vision\n- Applications include recommendation systems, autonomous vehicles, chatbots, and facial recognition\n- Challenges remain in bias mitigation, interpretability, and energy efficiency\n- Researchers are exploring novel architectures and training methods to improve capabilities\n- The future of AI involves specialized models, domain expertise integration, and responsible development",
"input_chars": 757,
"output_chars": 486
}Tags
x402
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