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Make Short

Community
hassancs91
make-short

Build a fully-synthetic vertical short (1080×1920, ~40s) end-to-end from a topic — script + beats.json, linked TSX beats over a persistent canvas, phone-scale QA, render, ElevenLabs voice with exact word-synced captions, SFX audition, optional music bed. Use when the user wants to "make a short", "create a shorts video", build a TSX short for a niche (chess, math, algorithms, dev tips, Excel…), add voice/captions to a short, or continue the short-N series in this repo. This is the 100%-TSX track — for video-model pixels use make-ai-short, for the paper-collage documentary look use make-vox. Defers raw TSX crash rules to vidtsx-2d-generator and SFX taste to suggest-sfx + brand §7.

Overview

Publisherhassancs91
Repositoryclaude-faceless-shorts-creator
Skill namemake-short
Stars
279
Forks
105
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by hassancs91 on GitHub. Read the source before you install it.

Installation

Install the Make Short AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/hassancs91/claude-faceless-shorts-creator/tree/main/.claude/skills/make-short
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/hassancs91/claude-faceless-shorts-creator.git /tmp/claude-faceless-shorts-creator
mkdir -p .claude/skills
cp -r /tmp/claude-faceless-shorts-creator/.claude/skills/make-short .claude/skills/make-short
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Make Short in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Make Short on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Make Short is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

make-short — fully-TSX vertical shorts, end to end

Everything is code: no footage, no stock. One short = one Remotion composition fed by a beats contract, with voice and SFX layered on after render. Proven across the 12 example shorts in shorts/. The idea bank + niche ranking lives in IDEAS.md — read it when picking a topic, and grow it when brainstorming.

Run everything from the repo root. Tools are stdlib-only Python 3.10+; ffmpeg/node must be on PATH; API keys live in .env (see .env.example).

Artifact contract

shorts/short-N-<niche>/
  script.md        — hook, beat sheet table (time | on screen | VO), production notes
  beats.json       — machine contract: format, vo[] (text+start/end+words), beats[], niche timeline
  voice/           — per-line TTS clips + voice.wav        (gen_voice.py)   [gitignored]
  sfx-plan.json    — cue sheet on the global timeline       (mix_sfx.py)
  output/          — short-N-sfx.mp4 (+ music auditions)                    [gitignored]
remotion/src/shots/short-N/
  ShortN<Name>.tsx — THE composition (registered by npm run gen)
  vo.gen.ts        — AUTO-GENERATED VO with exact word times (never hand-edit)

Shared kit: remotion/src/lib/shorts.tsx (Captions, Kicker, BigTitle, Stamp, PauseCard, StatChip, ProgressBar, ShortsBackdrop, SAFE areas, prog helper). Niche libs so far: lib/chess.tsx, lib/math.tsx, lib/algo.tsx, lib/sheet.tsx, lib/piano.tsx, lib/prob.tsx, lib/map.tsx, lib/orbit.tsx, lib/chart.tsx, lib/story.tsx… Add at most ONE new niche lib per short, generic enough for a series.

Stage 1 — script + beats

Beat grammar (~38–42s): HOOK (0–3.4s, frame 0 FULLY composed — the payoff already visible, no fade from black) → SETUP → optional QUIZ (PauseCard, ~2.5s — drives comments) → REVEAL in 2–4 steps, each synced to a VO word → TWIST → LOOP (last frame == frame 0, dissolving the payoff back into the intro so it replays seamlessly).

Outros — no fluff. NEVER end on an old-school engagement-CTA — no "what should I do next?", no "comment below", no "which one should I break down". They read as dated. End on the PAYOFF line, and let the visual LOOP blend back into the intro — the loop-into-intro is the ending. Prefer a clean visual dissolve/reset that lands the last frame exactly on frame 0. If a seamless loop genuinely isn't possible for a topic, just end on the payoff with no filler. Don't pad the tail: trim the composition so it ends shortly after the payoff, not seconds of dead air.

VO rules: ~100 words total, estimate line windows at ~2.7 words/sec with slack to the next line's start (tighter forces audible atempo squeeze — 3.3wps needed a 1.3× squeeze; 2.7wps peaked at 1.11×). Facts must be verified before scripting. Write script.md + beats.json (vo lines with estimated start/end; niche timeline in global SECONDS).

Stage 2 — the composition

  • One .tsx under remotion/src/shots/short-N/, compositionConfig 1080×1920 @30, ~42s. Follow vidtsx-2d-generator's hard rules (frame-based only, monotonic ranges, Easing.bezier).
  • Beats = <Sequence> scenes over ONE persistent canvas (the board/equation/array is the continuity — rewinds and evolutions happen in a single component's timeline, not cuts).
  • Captions lines={VO} + ProgressBar mounted at the ROOT (global time), scenes beneath.
  • THE recurring bug: frames inside a <Sequence> are LOCAL. Converting a global beat second to a scene cue is local_f = global_s*fps − sequence_from. Check every cue twice.
  • Frame-0 rule: hook scene uses warm props (BigTitle/EqRow) and negative ats so highlights/ stamps are already on at f0. Loop scene reverses the hook's punch-in (settle 1.06→1 vs grow 1→1.06) so the video loops seamlessly.
  • Safe areas: captions block centered ~y1500; nothing critical in bottom 340px / right 160px.

Stage 3 — QA (do not skip, it catches real bugs every time)

cd remotion && npm run gen        # frames.mjs does NOT run gen-registry itself
node scripts/frames.mjs ShortNName 0,<beat-boundaries+hero-frames>,<last> --scale=0.5

READ every PNG (phone scale). Checklist: frame 0 composed & thumbnail-grade · every reveal synced to its beat · nothing covering the payoff element · kickers swap with the narration · captions clear of UI zones · loop frame ≈ frame 0. Fix, re-render frames, only then:

node scripts/render-all.mjs ShortNName --scale=1     # -> remotion/out/ShortNName.mp4

Stage 4 — voice (ElevenLabs, word-exact captions)

python tools/gen_voice.py --beats shorts/short-N-<niche>/beats.json \
    --voice TX3LPaxmHKxFdv7VOQHJ --emit-ts remotion/src/shots/short-N/vo.gen.ts
  • Per-line TTS with /with-timestamps → REAL per-word times (tempo-scaled, global) written into beats.json AND vo.gen.ts. The shot imports { VO } from './vo.gen' — captions then highlight on the exact spoken word. Never estimate when a voice track exists.
  • Clips are cached by text-hash: rewriting one line only re-bills that line.
  • Voice: the examples use ElevenLabs premade "Liam" (TX3LPaxmHKxFdv7VOQHJ); swap in any voice (including your own clone) with the --voice flag + regen.
  • Then re-render the composition (captions retimed) and mux: ffmpeg -i remotion/out/<Id>.mp4 -i shorts/.../voice/voice.wav -map 0:v -map 1:a -c:v copy -c:a aac -b:a 192k -t 42 remotion/out/<Id>-voiced.mp4

Stage 5 — SFX (the suggest-sfx machinery, shorts flavor)

Read brand.md §7 + media/library/sfx/catalog.json. Library-first; add generic recipes to palette.json + python tools/gen_sfx.py only for genuine misses. Author shorts/short-N-<niche>/sfx-plan.json (preview = the -voiced.mp4, out = output/short-N-sfx.mp4).

Shorts taste adaptations: diegetic action sounds are the content (piece thocks, digit pops) and may exceed long-form density; decorative cues stay optional: true; layer the 2–3 hero moments (capture+stamp, carry flight+landing+chime). Cue times from EXACT landing frames: at_s = (move.at + move.dur + sequence_from) / fps.

PYTHONIOENCODING=utf-8 python tools/mix_sfx.py shorts/short-N-<niche>/sfx-plan.json --print
PYTHONIOENCODING=utf-8 python tools/mix_sfx.py shorts/short-N-<niche>/sfx-plan.json

The mix is an AUDITION — the user's ear is the audit gate before anything is called final. Update catalog used_in afterwards.

Stage 6 — music (optional, per video)

Library beds in media/library/music/ (gen_music.py to grow). Audition over the SFX mix: python tools/mix_music.py --all --base shorts/short-N-<niche>/output/short-N-sfx.mp4 (or --bed <id>). Hard-ducked under voice.

Done =

script.md + beats.json authored (facts verified) · composition QA'd frame-by-frame · rendered at scale 1 · voice generated with word-exact captions and muxed · SFX plan authored + audition mixed (~−15.5 LUFS, awaiting the user's ear) · library used_in updated · IDEAS.md queue updated.

Frequently asked questions

What does the Make Short AI skill do?

Build a fully-synthetic vertical short (1080×1920, ~40s) end-to-end from a topic — script + beats.json, linked TSX beats over a persistent canvas, phone-scale QA, render, ElevenLabs voice with exact word-synced captions, SFX audition, optional music bed. Use when the user wants to "make a short", "create a shorts video", build a TSX short for a niche (chess, math, algorithms, dev tips, Excel…), add voice/captions to a short, or continue the short-N series in this repo. This is the 100%-TSX track — for video-model pixels use make-ai-short, for the paper-collage documentary look use make-vox....

Why use Make Short on TypingMind?

Because you install it once and use it with any model. Make Short is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Make Short in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hassancs91/claude-faceless-shorts-creator/tree/main/.claude/skills/make-short. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Make Short?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Make Short?

As many as you like. As long as a model supports skills, you can use Make Short with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Make Short AI skill free?

Yes. It is published on GitHub by hassancs91 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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