Skills

Resolve Tighten Recording

Tightening one long single-take recording, talking-head, screencast, tutorial, podcast...

Install

npx skills add samuelgursky/davinci-resolve-mcp --skill resolve-tighten-recording -g -a claude-code -y
Category
AI and agents
Updated
3d ago
License
MIT
Context cost
Mediumabout 2,050 tokens
Runs scripts
No, instructions only

What it does

Tightening one long single-take recording, talking-head, screencast, tutorial, podcast video, by removing dead air in the DaVinci Resolve MCP. Apply when asked to tighten a recording, remove silences or dead air, cut the pauses out of a long take, or turn a raw one-take recording into a first cut. The subtractive counterpart to resolve-rough-cut, which selects shots from many clips; this skill removes time from one clip.

Resolve Tighten Recording

Turns one long raw take into a tightened variant timeline. The variant is the deliverable; the original timeline is never touched.

Everything below was measured live against Resolve Studio 21.0.1.11 / MCP v2.80.1 on 2026-08-06, on a real 28.5-minute 30fps screen recording, unless a different date is given.

The deliverable contract

Deliver a tightened variant timeline, plan → review → confirm. Do not grade, caption, or add anything; a tighten is pure subtraction. The variant runs generous on purpose, recovering over-cut material is slow and invisible, trimming further is fast and visible.

Two things always go back to the editor with the variant:

  • The largest lifts. A lift is only silence to the microphone. Measured on real material (2026-07-31): a 29s lift was 70% silent on-screen demonstration, real content, cut because nobody spoke over it. Anything over ~15s deserves a human look before the variant is trusted.
  • What silence-driven tightening cannot hear, see the last section.

Workflow

  1. Lift the analysis caps for long media, media_analysis set_caps_preset {preset: "unlimited"}. The standard preset carries a 90-second wall clock; multi-hour material dies on it. Restore standard when done (step 7).
  2. Transcribe, media_analysis start_batch_job with {clip_id, vision: false, transcription: {enabled: true, ...}}, then run_batch_job_slice {job_id}. Two traps in one call pair:
    • Batch jobs do not advance themselves. start_batch_job returns a durable job in queued and nothing runs until a slice call drives it.
    • run_batch_job_slice blocks until the slice completes, budget roughly 4-7x realtime for local whisper (measured: 28.5min of Chinese speech in 5m14s via mlx_whisper) and run it from a background process, not the main conversation.
Read the whole SKILL.md on GitHub

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