jikji
Non-destructive local file maps and instant search indexes for AI agents
Jikji find: local file discovery for AI agents 파일 하나 찾을 때마다 38,650 토큰, 57초, 11.7회 LLM 호출을 쓰던 raw agent 탐색을 줄이는 비파괴 로컬 탐색 스킬 같은 551건에서 Jikji find는 파일 하나당 447 토큰, 2.1초, 1회 호출로 더 높은 Hit@1을 냈다.
⚡ 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/nomadamas-jikji — read its card at https://meshkore.com/agent/nomadamas-jikji/.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/nomadamas-jikjiFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/nomadamas-jikji/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Do you own jikji?
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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