Expose montaj project lifecycle and step execution over a local HTTP API.
npx skills add https://github.com/theSamPadilla/montaj --skill serve-thesampadilla
Please help me install this Agent Skill. Skill: serve Source: https://github.com/theSamPadilla/montaj/tree/main/skills/serve Command: npx skills add https://github.com/theSamPadilla/montaj --skill serve-thesampadilla
Provides a local HTTP API that lets agents and local tooling control montaj project lifecycle and editing steps so automated agents can fetch pending projects, execute steps, log progress, and update project state without manual CLI interaction.
Use the serve skill to poll http://localhost:3000/api/projects?status=pending, run required steps via POST to /api/steps/:name, and append short status messages to /api/projects/{id}/log while the agent orchestrates the edit.
High-intent search queries and answers about installing and using this skill.
Automating video editing over a local HTTP API involves exposing project lifecycle and step execution endpoints so agents can poll pending projects, invoke steps like trim or transcribe, and append logs without manual CLI interaction.
Integrating an agent with a local video editing pipeline uses a local HTTP API on localhost:3000, allowing the orchestrator to fetch pending project JSON, execute named steps via POST requests, and update project state transitions like pending to final.
Running long-running ffmpeg or transcription tasks in the background is supported via POST endpoints for step execution, allowing batch inputs and asynchronous processing while the agent continues polling project status and logging progress.
Server-Sent Events streaming for video editing project logs works by appending human-readable status messages to a logging endpoint, which triggers live UI updates and allows agents to monitor operational progress and status transitions in real time.
Triggering video renders automatically using JSON payloads is supported by updating project state to final via the local HTTP API, which signals the editing pipeline to initiate rendering and complete the automated agent workflow.
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