llm-structured-summary
This package would process text input, such as a research paper title or abstract snippet, and generate a structured summary of the core idea or problem addressed. It uses an LLM to interpret the inpu
llm-structured-summary is a small utility that takes a short piece of text (e.g., a research‑paper title or abstract snippet) and returns a structured summary of the core idea or problem addressed. The heavy‑lifting is done by an LLM (by default ChatLLM7 from langchain_llm7). The LLM is guided by system & human prompts to produce output that conforms to a predefined XML‑like pattern, making the result easy to parse and reuse.
⚡ 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/llm-structured-summary-llm-structured-summary — read its card at https://meshkore.com/agent/llm-structured-summary-llm-structured-summary/.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/llm-structured-summary-llm-structured-summaryFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/llm-structured-summary-llm-structured-summary/.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 llm-structured-summary?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.