Autoshorts
Upload-Post/skill-autoshorts
Daily pipeline that picks one long video from a folder, transcribes it with Whisper, uses Gemini 3 Flash multimodal to find every viral short-form moment, cuts each candidate with FFmpeg, adds a…
Cuts long-form video into short platform-ready clips: finds strong moments, reframes for vertical, adds subtitles and brand overlays, and writes a clip manifest.
Install Video Clip Repurposing
$ npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install pawbytes/skill-suites paw-cra-video-clips --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/pawbytes/skill-suites.git skills-src && mkdir -p .claude/skills && cp -r skills-src/src/creative/paw-cra-video-clips .claude/skills/paw-cra-video-clips && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "paw-cra-video-clips" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/creative/paw-cra-video-clips into .claude/skills/paw-cra-video-clips/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-cra-video-clips", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/pawbytes/skill-suites/tree/main/src/creative/paw-cra-video-clipsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install pawbytes/skill-suites paw-cra-video-clips --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pawbytes/skill-suites.git skills-src && mkdir -p .agents/skills && cp -r skills-src/src/creative/paw-cra-video-clips .agents/skills/paw-cra-video-clips && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "paw-cra-video-clips" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/creative/paw-cra-video-clips into .agents/skills/paw-cra-video-clips/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-cra-video-clips", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install pawbytes/skill-suites paw-cra-video-clips --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pawbytes/skill-suites.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/src/creative/paw-cra-video-clips .cursor/skills/paw-cra-video-clips && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "paw-cra-video-clips" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/creative/paw-cra-video-clips into .cursor/skills/paw-cra-video-clips/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-cra-video-clips", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/pawbytes/skill-suites.git --path src/creative/paw-cra-video-clips--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install pawbytes/skill-suites paw-cra-video-clips --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pawbytes/skill-suites.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/src/creative/paw-cra-video-clips .gemini/skills/paw-cra-video-clips && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "paw-cra-video-clips" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/creative/paw-cra-video-clips into .gemini/skills/paw-cra-video-clips/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-cra-video-clips", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install pawbytes/skill-suites paw-cra-video-clipsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/pawbytes/skill-suites.git skills-src && mkdir -p .github/skills && cp -r skills-src/src/creative/paw-cra-video-clips .github/skills/paw-cra-video-clips && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "paw-cra-video-clips" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/creative/paw-cra-video-clips into .github/skills/paw-cra-video-clips/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-cra-video-clips", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install pawbytes/skill-suites paw-cra-video-clips --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pawbytes/skill-suites.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/src/creative/paw-cra-video-clips .opencode/skills/paw-cra-video-clips && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "paw-cra-video-clips" agent skill from https://github.com/pawbytes/skill-suites/tree/main/src/creative/paw-cra-video-clips into .opencode/skills/paw-cra-video-clips/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "paw-cra-video-clips", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
paw-cra-video-clips- GitHub stars
- 113
- Token cost
- ~1.2k tokens
- SKILL.md length
- 488 words
- Files
- 10 (incl. scripts, references)
- Skills in repo
- 71
- Repo updated
- First seen
- Licence
- MIT
At a glance
Cuts long-form video into short platform-ready clips: finds strong moments, reframes for vertical, adds subtitles and brand overlays, and writes a clip manifest.
- Turning a long webinar or interview recording into short social clips
- SKILL.md covers Overview, On Activation, Pipeline and Platform Encoding Reference, plus 2 more sections
- Runs Python scripts from its folder; calls ffmpeg and ffprobe
- Reframing landscape footage to vertical with subtitles and brand overlays
What it does
This workflow takes a long video, looks for high-value moments, extracts clips at target durations, reframes them for vertical platforms, adds subtitles and brand overlays, and encodes each clip to the specs of its destination platform. It needs a source video path and a brand name at a minimum, and accepts a --headless (or -H) flag to run without interaction and auto-approve the review gate.
The output is a set of clip files plus a clip-manifest.json, saved in the brand's videos/clips folder under .pawbytes/creative-suites. Reference notes cover source intake, analysis, clip production, manifest and review, export and platform specs, and a Python script generates the manifest. Brand guidelines and shared agency memory are loaded when they exist.
ffmpeg and ffprobe are required, and the workflow stops if ffmpeg is missing. OpenShorts, run through Docker or a local install, improves moment detection but is optional because ffmpeg alone is a fallback. A fal.ai key is optional and only used for AI upscaling.
When your agent uses it
- Turning a long webinar or interview recording into short social clips
- Reframing landscape footage to vertical with subtitles and brand overlays
- Producing platform-specific exports from one source video in a single run
Example prompts
- “Extract clips from recordings/q3-webinar.mp4 for the Northwind brand.”
- “Repurpose this founder interview into short vertical clips with subtitles.”
- “Run the clip pipeline headless on talk.mp4 for the Acme Tools brand.”
Requirements
- ffmpeg and ffprobe
- A source video file and a brand name
- OpenShorts via Docker or a local install (optional)
- A fal.ai API key for AI upscaling (optional)
What it can do on your machine
Read from SKILL.md and the folder at commit 547a6df. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
ffmpegffprobe
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Video Clip Repurposing loads about 1.2k tokens when it runs, and up to ~6.2k if it reads all its reference files. Until then it costs about 51 tokens; SKILL.md has 488 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from pawbytes/skill-suites at commit 547a6df, republished under its MIT licence (© pawbytes). 488 words, ~1,173 tokens.
Download SKILL.mdSave it as
.claude/skills/paw-cra-video-clips/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.- name
- paw-cra-video-clips
- description
- Video repurposing pipeline for multi-platform clip extraction. Use when the user requests to 'extract clips', 'repurpose video', 'create clips from video', or 'clip video for social'.
Video Clips
Overview
This workflow extracts short, platform-ready clips from long-form video content. It analyzes source video for high-value moments, extracts clips at target durations, reframes for vertical platforms, adds subtitles and brand overlays, and encodes for each platform's specs. Every clip is production-ready for upload.
Args: Accepts --headless / -H for non-interactive execution. Requires source video path and brand name at minimum.
Output: Platform-ready clip files + clip-manifest.json in .pawbytes/creative-suites/brands/{brand-name}/videos/clips/.
Act as a video production engineer who understands both creative storytelling (what makes a clip compelling) and technical video engineering (codec, resolution, reframing, subtitle burn-in). You know what goes viral and what meets platform specs.
On Activation
Load available config from {project-root}/.pawbytes/config/config.yaml and {project-root}/.pawbytes/config/config.user.yaml (root level and cra section). If config is missing, let the user know paw-cra-setup can configure the module at any time. Use sensible defaults for anything not configured.
Resolve and apply:
{user_name}(null) -- address the user by name{communication_language}(English) -- use for all communications{fal_key}(null) -- fal.ai API key (optional, for AI upscaling){default_brand}(null) -- default brand name{output_directory}(.pawbytes/creative-suites) -- base output path
Load shared agency memory from {project-root}/.pawbytes/creative-suites/index.md if it exists. Load brand guidelines from .pawbytes/creative-suites/brands/{brand}/guidelines.md when brand is known.
Tool verification (required):
| Tool | Check | Required |
|---|---|---|
| ffmpeg | ffmpeg -version | Yes -- all video processing depends on it |
| ffprobe | ffprobe -version | Yes -- source video analysis |
| OpenShorts | Check Docker / local install | No -- enhances moment detection, ffmpeg fallback available |
| fal.ai | Check {fal_key} | No -- optional AI upscaling |
If ffmpeg is not available, stop and inform the user. Without ffmpeg, this workflow cannot function.
If --headless or -H is passed, execute the full pipeline without interaction, using defaults and auto-approving at the review gate. Otherwise, proceed interactively through each stage.
Show full SKILL.md (210 more words)Show less
Pipeline
Source Intake --> Analysis --> Clip Production --> Manifest & Review --> Export
[1] [2] [3-7] [8-9] [10-11]| Stage | Load | Headless Behavior |
|---|---|---|
| Source Intake | ./references/01-source-intake.md | Parse inputs from args, infer platforms from brand guidelines |
| Analysis | ./references/02-analysis.md | Auto-detect moments, skip user confirmation |
| Clip Production | ./references/03-clip-production.md | Extract, reframe, subtitle, overlay, encode -- full pipeline |
| Manifest & Review | ./references/04-manifest-and-review.md | Generate manifest, auto-approve |
| Export | ./references/05-export.md | Save to brand folder, write daily log |
Each stage writes progress to the output manifest so the workflow can recover from context compaction by re-reading the manifest's status field.
Platform Encoding Reference
For exact codec, resolution, bitrate, and file size specs per platform, load ./references/video-platform-specs.md. This is the authoritative reference for all encoding decisions.
Manifest Generation
Run ./scripts/generate-clip-manifest.py --help for interface details. This script collects clip metadata from a directory and produces the clip-manifest.json. Use it after all clips are encoded.
Key Principles
- Production-first -- every clip must be immediately uploadable to its target platform
- Subtitles always -- burned-in subtitles on every clip for accessibility and engagement
- Brand consistency -- watermarks, intros, end cards per brand guidelines
- Smart reframing -- vertical clips must focus on the speaker/action, not blindly center-crop
- Manifest everything -- every clip tracked with timestamps, source timecodes, platform, and specs
- Retry on transient failure -- if a clip extraction or encoding step fails with a transient error (ffmpeg I/O error, API timeout/429/5xx), retry once after 5 seconds before marking as failed
© pawbytes, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 9 other files (scripts, references) in src/creative/paw-cra-video-clips of pawbytes/skill-suites.
- SKILL.md
- references/01-source-intake.md
- references/02-analysis.md
- references/03-clip-production.md
- references/04-manifest-and-review.md
- references/05-export.md
- references/video-platform-specs.md
- scripts/__pycache__/generate-clip-manifest.cpython-314.pyc
- scripts/generate-clip-manifest.py
- scripts/tests/test-generate-clip-manifest.py
Open the folder on GitHubat commit 547a6df
Compare with similar skills
Video Clip Repurposing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Video Clip Repurposing this skillpawbytes/skill-suites | 113 | — | ~1.2k | Automated safety check: Pass | MIT | |
| AutoshortsUpload-Post/skill-autoshorts | 151 | — | ~5.3k | Automated safety check: Notes | MIT | |
| KinocutKyaniteLabs/kinocut | 198 | — | ~5.7k | Automated safety check: Pass | Apache-2.0 | |
| Stage EditOrkas-AI/Orkas-VideoStudio | 499 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Kinocut RepurposeKyaniteLabs/kinocut | 198 | — | ~1k | Automated safety check: Pass | Apache-2.0 | |
| AI-Assisted Video Editingaffaan-m/ECC | 276k | 4 repos | ~2.9k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Video Clip Repurposing
What does Video Clip Repurposing do?
Cuts long-form video into short platform-ready clips: finds strong moments, reframes for vertical, adds subtitles and brand overlays, and writes a clip manifest. This workflow takes a long video, looks for high-value moments, extracts clips at target durations, reframes them for vertical platforms, adds subtitles and brand overlays, and encodes each clip to the specs of its destination platform. It needs a source video path and a brand name at a minimum, and accepts a --headless (or -H) flag to run without interaction and auto-approve the review gate.
When should I use Video Clip Repurposing?
Video Clip Repurposing fits situations like: turning a long webinar or interview recording into short social clips; reframing landscape footage to vertical with subtitles and brand overlays; producing platform-specific exports from one source video in a single run.
How do I install Video Clip Repurposing in Claude Code?
Run `npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a claude-code`. Or copy the skill folder (src/creative/paw-cra-video-clips in pawbytes/skill-suites) into .claude/skills/paw-cra-video-clips in your project. Claude Code loads it when a task matches its description.
How do I install Video Clip Repurposing in Codex?
Run `npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a codex`. Or copy the skill folder (src/creative/paw-cra-video-clips in pawbytes/skill-suites) into .agents/skills/paw-cra-video-clips in your project. Codex loads it when a task matches its description.
Can I use Video Clip Repurposing in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pawbytes/skill-suites --skill paw-cra-video-clips -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/paw-cra-video-clips, .gemini/skills/paw-cra-video-clips, .github/skills/paw-cra-video-clips and .opencode/skills/paw-cra-video-clips in your project.
What does Video Clip Repurposing need to run?
Going by SKILL.md and its folder, Video Clip Repurposing needs Python for the scripts in its folder and the command-line tools its instructions call (ffmpeg and ffprobe). Our summary lists: ffmpeg and ffprobe; A source video file and a brand name; OpenShorts via Docker or a local install (optional); A fal.ai API key for AI upscaling (optional).
Does Video Clip Repurposing access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Video Clip Repurposing safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Video Clip Repurposing use?
Video Clip Repurposing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Video Clip Repurposing use?
About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5k tokens, read only when the agent opens those files.
What are the alternatives to Video Clip Repurposing?
Skills that share tags, products or a category with Video Clip Repurposing: Autoshorts (Upload-Post/skill-autoshorts, 151 stars), Kinocut (KyaniteLabs/kinocut, 198 stars), Stage Edit (Orkas-AI/Orkas-VideoStudio, 499 stars) and Kinocut Repurpose (KyaniteLabs/kinocut, 198 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Video Clip Repurposing?
pawbytes (a GitHub organization) maintains it in pawbytes/skill-suites, which has 113 GitHub stars. The repository holds 71 skills in this directory. The repository was last updated on October 3, 2026.
Source: pawbytes/skill-suites on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.