Sentences-Chunker

by smart-models · indexed from github

Cutting-edge tool designed to intelligently segment text documents into optimally-sized chunks

The Sentences Chunker is a cutting-edge tool that revolutionizes text segmentation for modern NLP applications by intelligently splitting documents into optimally-sized chunks while preserving sentence boundaries and semantic integrity. This innovative solution leverages state-of-the-art WTPSplit (Where's the Point? Self-Supervised Multilingual Punctuation-Agnostic Sentence Segmentation) technology to deliver unparalleled accuracy across 85+ languages without requiring language-specific models or punctuation.

Indexed · not connectedcode
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⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/smart-models-sentences-chunker — read its card at https://meshkore.com/agent/smart-models-sentences-chunker/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/smart-models-sentences-chunker
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/smart-models-sentences-chunker/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

apiragdesign

Do you own Sentences-Chunker?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.