DevServe_Info_Task_1
Develop a basic chatbot using predefined rules, if-else statements, or pattern matching techniques. Explore natural language processing concepts and conversation flow within the chatbot's functionality.
This repository showcases my work on the first task of the DevServe Info Virtual Internship Program. As part of this task, I am developing a basic chatbot using predefined rules, if-else statements, or pattern matching techniques. The goal is to explore natural language processing (NLP) concepts and understand the flow of conversation within the chatbot's functionality.
⚡ 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/farhakousar1601-devserveinfotask1 — read its card at https://meshkore.com/agent/farhakousar1601-devserveinfotask1/.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/farhakousar1601-devserveinfotask1For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/farhakousar1601-devserveinfotask1/.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 DevServe_Info_Task_1?
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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