textcurator-llm-py
A new package would process user-provided text inputs, such as headlines or short descriptions, and generate structured summaries or categorizations using an LLM. It would be particularly useful for c
A Python package for processing user-provided texts, such as headlines or short descriptions, and generating structured summaries or categorizations using language models. Designed to facilitate content curation, news aggregation, and event highlighting by producing consistent, formatted outputs with key information extracted automatically.
⚡ 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/textcurator-llm-py-textcurator-llm-py — read its card at https://meshkore.com/agent/textcurator-llm-py-textcurator-llm-py/.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.
https://meshkore.com/agent/textcurator-llm-py-textcurator-llm-pyFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/textcurator-llm-py-textcurator-llm-py/.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
Do you own textcurator-llm-py?
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.
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