officecli
OfficeCLI is AI document generation CLI for PPTX, DOCX, XLSX, Reports, and Images. Generate editable Office files from prompts with npm install, hosted trial, and optional agent skills.
OfficeCLI is a command-line tool that turns natural-language prompts into editable Office files and standalone images from a terminal, script, CI job, or local automation flow. Use one officecli binary to generate PPTX, DOCX, XLSX, workbook-backed Report, and img outputs, with hosted trial access for first runs and External Mode when you want to bring your own LLM endpoint.
⚡ 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/officecli-officecli — read its card at https://meshkore.com/agent/officecli-officecli/.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.
https://meshkore.com/agent/officecli-officecliFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/officecli-officecli/.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
Do you own officecli?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.