I Built an Editable Timeline for AI Agents: Skills, MCP, and Transactional Video Editing

Description and use

An editable video timeline system allows AI agents to incrementally edit projects, preserving metadata, validating plans, previewing diffs, and applying changes transactionally.

Problem

AI agents can generate FFmpeg commands, but they lack a way to edit a project incrementally, preserve state, and provide a reusable, inspectable plan for subsequent edits.

Outcome

The architecture enables agents to perform incremental, reversible edits on a video project while preserving all necessary metadata, enforcing preconditions, and providing a dry‑run diff before applying changes. It supports idempotent retries, revision checks, and transactional application to avoid partial edits.

Workflow

• Inspect project state
• Agent analyzes media and generates a structured edit plan
• Validate plan against project preconditions
• Generate a semantic diff to preview changes
• Apply the plan transactionally to produce a new project archive
• Re‑inspect the updated project

Evidence

A rendered MP4 does not preserve the decisions needed for the next edit: clip identity, source ranges, timing, transforms, and caption/audio relationships.

Source

Timeline Studio uses an editable .timeline project as the source of truth.

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The workflow is: inspect -> plan -> validate -> diff -> apply -> inspect

Source

The local CLI and MCP writes also require a new output path and reject overwriting the input or an existing output.

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