automate-tech-post

by lfunderburk · indexed from github

LLM application: fine tuned model to generate social media posts from technical blogposts. I used the documentation in https://numpy.org/numpy-tutorials/index.html to build a synthetic dataset and used that dataset to fine-tune an open source model.

The purpose of this repository is to demonstrate how you can leverage two techniques when summarizing and transforming content from open source blogs to generate social media posts.

Indexed · not connectedcontent
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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 · 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/lfunderburk-automate-tech-post — read its card at https://meshkore.com/agent/lfunderburk-automate-tech-post/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/lfunderburk-automate-tech-post
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lfunderburk-automate-tech-post/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

llmblogfine-tundatasocial

Do you own automate-tech-post?

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.