tighten
Skill0 starsChanged 48 days agoApache-2.0View on GitHub
Tighten talking-head footage from its transcript - shorten long pauses, cut filler words (um, uh), and drop false starts and retakes - as a new, cleaned copy of the clip. Use when the user runs /video-studio:tighten, or asks to clean up a recorded talk, demo narration or interview before making shorts or a reel.
10 other projects use a version of this.
Adopted by
Most recently taken up by
- aditya-vermax/skillstheir own version, first seen Nov 8, 2026
- nearmap/shipyardtheir own version, first seen Nov 8, 2026
- nuko-nova-dynamics/nuko-nova-unsloptheir own version, first seen Nov 6, 2026
- wtsi-hgi/agentskillstheir own version, first seen Nov 1, 2026
- oneafrikan/the-gridtheir own version, first seen Oct 20, 2026
- captkernel/claude-writing-toolstheir own version, first seen Oct 15, 2026
Other versions10 projects use a version of this.
Word for word · 0
None found.
Edited · 0
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Wrote their own version · 10
- autobrr/mkbrr★ 363same name
- oneafrikan/the-grid★ 4same name
- aditya-vermax/skills★ 1same name
- corygabrielsen/skills★ 1same name
- markrogersjr/skills★ 1same name
- nearmap/shipyard★ 1same name
- nuko-nova-dynamics/nuko-nova-unslop★ 1same name
- wtsi-hgi/agentskills★ 1same name
- captkernel/claude-writing-tools★ 0same name
- raj-khan/tighten★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository24 other files it gives its agents.
The file
Files
Tighten a recording
- The recording must be ingested and transcribed (
ingest, thentranscribe; ask before any whisper model download). Use its asset id. - Dry run:
tighten {project_dir, asset}. Show the user the summary: total length before → after, pauses shortened, and every filler and retake cut with its time and words. Also show the join check (joins): everypartial_word(a cut inside a word) andrepeated_word(the same word on both sides of a join) with its time and fix (the cut moved to the nearest word gap). - Let the user adjust before applying:
- "keep the pauses" →
silences: false, or a gentlermax_pause_ms: 1200 - "pace it like my other videos" →
pacing_from: ananalyzeresult in the project (qa/analysis.json, from a video the user edited) or the asset id of such a video. It setsmax_pause_msto their p95 pause (clamped to 250–1500 ms) andkeep_pause_msto their median pause (120–600 ms); explicit values win. Report the numbers (pacing). - "don't cut retakes" →
retakes: false, if a "false start" was intentional - a retake detection that is wrong: turn retakes off; never hand-edit cuts
- "keep the pauses" →
- Apply:
tighten {project_dir, asset, …same options, apply: true}. It writes a new asset<asset>-tight(the original is kept) with the transcript re-timed, so captions andclaim_refsline up with the new cut.- Apply refuses while a
partial_wordremains. Usually the transcript's timings are off there: re-transcribe, or change the options. Passforce: trueonly when the user has heard the join and accepts it. - With whisper installed, apply re-transcribes ±2 s around every join
(
asr_check): report eachjoin_mismatch(expected vs heard words) so the user can listen to it.not_rungives the reason (no whisper, no model); it is not an error.
- Apply refuses while a
- Next:
shortsor a talking-head / silent-vlog spec on<asset>-tight. Suggest watching the tightened clip once: word-timing cuts are precise to whisper's timestamps, and a rare cut can clip the edge of a word that the join check cannot see. For a video, thecompareskill builds a before/after page for that:a: {file: <the original's project-relative path>}againstb: {file: <the path tighten returned, source/assets/<asset>-tight.mp4>}, played in sync, so the user can hear each cut against the original.
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