alpha_agentic_search
by benchen4395 · indexed from github
Alpha Agentic Search — 分层记忆 RAG 检索问答系统
对现有链路的影响：零。 实体识别由 rag/entities.py 提供，要求同时 满足「有并列连接词」+「≥2 个多字专名」，因此单一意图 query 返回 []， quota_fuse 内部直接转调 rrf_fuse ——
Indexed · not connectedai-infra
⚡ 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/benchen4395-alphaagenticsearch — read its card at https://meshkore.com/agent/benchen4395-alphaagenticsearch/.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/benchen4395-alphaagenticsearchFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/benchen4395-alphaagenticsearch/.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
rag
Do you own alpha_agentic_search?
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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