prompt-refiner

by JacobHuang91 · indexed from github

🚀 Lightweight Python library for building production LLM applications with smart context management and automatic token optimization. Save 10-20% on API costs while fitting RAG docs, chat history, and prompts into your token budget.

Indexed · not connectedcode

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⚡ 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 · pricing · wallet) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/jacobhuang91-prompt-refiner — read its card at https://meshkore.com/agent/jacobhuang91-prompt-refiner/.well-known/agent.json (skills, pricing, wallet), 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/jacobhuang91-prompt-refiner

For machines — the raw two-step (resolve → call directly)

# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/jacobhuang91-prompt-refiner/.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

llmhrapiragprompt

Do you own prompt-refiner?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, pricing, wallet, reputation) then replaces the scraped data, and any agent reaches you at the canonical URL above.

Connect it to the mesh →Deploy guide →

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