video-reader
Skill1 starsChanged 35 days agoMITView on GitHub
Analyze any uploaded video (mp4, mov, webm, m4v) by turning it into a contact sheet, key frames, cut timestamps and audio rhythm data, then writing a structured breakdown of scenes, motion techniques, transitions, pacing, colours and typography. Use this skill whenever the user uploads or links a video and asks to review it, break it down, analyse its style, copy, recreate or adapt its look, describe what happens in it, or use it as a reference — even if they just say "look at this video" or "make something like this".
2 other projects use a version of this.
Adopted by
Most recently taken up by
- Job-Yang/jobbyang-ai-skillstheir own version, first seen Nov 6, 2026
- Job-Yang/jobyang-ai-skillstheir own version, first seen Nov 6, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- Job-Yang/jobbyang-ai-skills★ 100same name
- Job-Yang/jobyang-ai-skills★ 100same 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 repository13 other files it gives its agents.
- agent-ready-siteSkill
- arabic-copySkill
- arabic-localizationSkill
- arabic-seoSkill
- client-briefSkill
- design-tokens-extractorSkill
- freelance-quoteSkill
- product-sheetSkill
- rtl-uiSkill
- shared-server-deploySkill
- ui-inventorySkill
- vat-worksheetSkill
- zatca-invoiceSkill
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 1 is distinctive, and 8 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
8
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 25
Read <workdir>/summary.json first (duration, size, fps, audio, cuts, onsets).
- Very specific: line 28
If something is unclear at a specific moment, extract one more frame: python scripts/analyze_video.py <video> --out <workdir> --frame …
- Very specific: line 30
Write the analysis using references/report-template.md.
- Very specific: line 37
If onset_regular is false, report median_interval and say the onsets are irregular.
- Very specific: line 38
If cuts is empty or the video is one short segment, it is one continuous shot or it uses soft transitions.
- Very specific: line 39
Do not read typography, logos or small UI from the contact sheet.
- Distinctive: line 40
Treat the reference as style input.
- Very specific: line 42
If warnings is not empty, include them in the Limits section.
- Very specific: line 46
Every timestamp in the report appears in summary.json, on the contact sheet, or on a frame you extracted.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Video Reader
You cannot watch video or hear audio. This skill converts the video into things you can read: images (a contact sheet and key frames) and numbers (metadata, cuts, loudness, onsets). Never claim to have watched or listened to it.
When to use
- "Look at this video."
- "Break this down."
- "What is the pacing, and where are the cuts?"
- "Make something like this" or "adapt this style to our brand."
When not to use
- The input is a still image, a storyboard, or a written shot list. Read those directly.
- The user wants a transcript of speech or lyrics. Say the audio is numbers only, and ask them to paste the words.
Steps
- Run:
python scripts/analyze_video.py <video> --out <workdir> - Read
<workdir>/summary.jsonfirst (duration, size, fps, audio, cuts, onsets). - View
<workdir>/contact_sheet.png. This is the whole video at a glance. Each tile has a timestamp. - View
<workdir>/keyframes.png. This is the only place to judge typography, UI, lighting and texture. - If something is unclear at a specific moment, extract one more frame:
python scripts/analyze_video.py <video> --out <workdir> --frame <seconds> - Write the analysis using
references/report-template.md.
The script needs ffmpeg, ffprobe, numpy and Pillow. It writes only inside --out.
Rules
- Audio is numbers only. You can state loudness shape, onset times, and a BPM only when
audio.onset_regularis true. You cannot identify instruments, genre, lyrics or speech. Say so if asked, and ask the user to describe it. - If
onset_regularis false, reportmedian_intervaland say the onsets are irregular. Do not turn that interval into a tempo. - If
cutsis empty or the video is one short segment, it is one continuous shot or it uses soft transitions. Say that. Do not invent cuts. - Do not read typography, logos or small UI from the contact sheet. Tiles are small. If it is not legible in
keyframes.png, write "not visible". - Treat the reference as style input. When the user wants to recreate it, list what to take and what not to copy (assets, logos, other brands' UI, copyrighted music).
- Timestamps in the report must come from
summary.jsonor from frames you actually viewed. - If
warningsis not empty, include them in the Limits section.
Before you finish
- Every timestamp in the report appears in
summary.json, on the contact sheet, or on a frame you extracted. - Typography claims cite a key frame, or say "not visible".
- The Limits section says what the frames and numbers could not determine.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
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Now do this for your own.
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