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abu-shotai

Ai Video Remix

by Yoki · GitHub ↗ · v0.1.3 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install ai-video-remix
Description
AI-driven video remix generator that uses ShotAI semantic search + LLM planning + Remotion rendering to produce styled video compositions from a user's local...
README (SKILL.md)

AI Video Remix Skill

This is an instruction-only skill — it provides guidance and reference documentation for the AI Video Remix CLI tool. The runtime source code lives in the GitHub repository and must be cloned separately (see Quick Start below).

Generate styled video compositions from a local ShotAI video library using natural language.

Important: Video Library Requirement

This skill can only search and use videos that have been imported into ShotAI. Videos simply stored on your hard drive are not searchable — they must be added to a ShotAI collection and fully indexed first.

Before using this skill, make sure you have:

  1. Opened ShotAI and created a collection
  2. Added your video files or folders to the collection
  3. Waited for indexing to complete (shot detection + semantic analysis — progress is shown in ShotAI)

If the search returns no results or low-quality matches, the most common reason is that the relevant videos have not been imported into ShotAI yet.

Prerequisites

See references/setup.md for full installation instructions, including:

  • ShotAI download and setup
  • ffmpeg installation
  • yt-dlp installation (for auto music)
  • Node.js dependencies

Quick Start

Note: This skill does not bundle runtime code. Clone the source repository first.

git clone https://github.com/abu-ShotAI/ai-video-remix.git
cd ai-video-editor
npm install
cp .env.example .env    # fill in SHOTAI_URL, SHOTAI_TOKEN, and optionally AGENT_PROVIDER
npx tsx src/skill/cli.ts "帮我做一个旅行混剪"

Pipeline (8 steps)

  1. Agent: parseIntent — LLM extracts theme, selects composition, optionally overrides music style
  2. Agent: refineQueries — LLM rewrites per-slot search terms to match library content
  3. ShotAI: pickShots — Semantic search per slot via local ShotAI MCP server (localhost only), best shot selected
  4. Music: resolveMusic — Uses local MP3 via --bgm (recommended), or optionally downloads from YouTube via yt-dlp
  5. ffmpeg: extractClip — Each shot trimmed to independent .mp4 clip file (local processing only)
  6. Agent: annotateClips — LLM assigns per-clip visual effect params (tone, dramatic, kenBurns, caption)
  7. File Server — Localhost-only HTTP server (127.0.0.1) serves clips to Remotion renderer within the same machine
  8. Remotion: render — Composition rendered to final MP4

CLI Usage

After cloning the repository and running npm install:

npx tsx src/skill/cli.ts "\x3Crequest>" [options]

Options:
  --composition \x3Cid>   Override composition (skip LLM selection)
  --bgm \x3Cpath>         Local MP3 path (skip YouTube search)
  --output \x3Cdir>       Output directory (default: ./output)
  --lang \x3Czh|en>       Output language: zh Chinese (default) / en English
                       Affects: video title, per-clip captions & location labels, attribution line
  --probe              Scan library first, let LLM plan slots from actual content

Compositions

ID Label Best For
CyberpunkCity 赛博朋克夜景 Neon city, night scenes, sci-fi
TravelVlog 旅行 Vlog Multi-city travel with location cards
MoodDriven 情绪驱动混剪 Fast/slow emotion cuts
NatureWild 自然野生动物 BBC nature documentary style
SwitzerlandScenic 瑞士风光 Alpine/scenic travel with captions
SportsHighlight 体育集锦 ESPN-style with goal captions

Modes

Standard mode (default): LLM picks composition + generates search queries from registry templates.

Probe mode (--probe): Scans library videos first (names, shot samples, mood/scene tags), then LLM generates custom slots tailored to what actually exists.

Choose probe mode when: library content is unknown, user wants "best of my library", or standard slots return low-quality shots.

Environment Variables

See references/config.md for all environment variables and LLM provider setup.

Troubleshooting & Quality Tuning

See references/tuning.md for solutions to:

  • Clip boundary flicker / 1–2 frame flash at cuts
  • Red flash artifact in CyberpunkCity (GlitchFlicker on short clips)
  • Low-quality or off-topic shots
  • Music download failures

Recommended .env defaults for best quality:

MIN_SCORE=0.5    # filter short/low-quality shots

Writing ShotAI Search Queries

ShotAI uses semantic search powered by AI-generated tags and embedding vectors. Query quality is the single biggest factor in shot relevance — invest time here.

Query construction rules

Always write full sentences or rich phrases, never bare keywords.

The search engine understands semantic similarity ("ocean" matches "sea", "waves", "shoreline"), so richer context produces better recall.

Quality Example When to use
⭐ Detailed description "A white seagull with spread wings gliding smoothly over calm blue ocean water, golden sunset light reflecting on the waves" Best precision — use for hero shots
⭐ Full sentence "A seagull flying gracefully over the ocean at sunset" Good balance of precision and recall
Short phrase "seagull flying over ocean" Acceptable fallback
Single keyword "seagull" Avoid — low precision, noisy results

What to include in a query

Describe the visual content of the ideal shot across these dimensions:

  • Subject: what/who is in frame (a lone hiker, city traffic at night, athlete celebrating)
  • Action: what is happening (walking slowly through fog, speeding through intersection, jumping with arms raised)
  • Environment: location, setting, time of day (rain-soaked Tokyo street, mountain meadow at golden hour, empty stadium under floodlights)
  • Mood / atmosphere: emotional tone (melancholic, tense, euphoric, serene)
  • Camera feel: implied movement or framing (wide establishing shot, tight close-up, slow pan, handheld shaky)

Not all dimensions are needed every time — include whichever are most distinctive for the shot you want.

The refineQueries step

When the agent runs refineQueries, it rewrites the composition's default slot queries to better match the user's actual library. Apply these principles:

  1. Start from the slot's semantic intent — what emotional or narrative role does this shot play in the composition?
  2. Incorporate any context from the user's request — location names, event names, specific subjects mentioned
  3. Expand synonyms — if the slot says "water", try "river flowing through forest" or "lake reflecting mountains" based on what the library likely contains
  4. Avoid negations"not indoors" does not work; instead describe the positive version ("outdoor daylight scene")
  5. One query per slot — make it specific rather than trying to cover multiple scenarios

Examples: slot query → refined query

Slot default: "city at night"
User request: "帮我做一个东京旅行混剪"
Refined:      "Neon-lit Tokyo street at night, pedestrians crossing under glowing signs, rain reflections on pavement"

Slot default: "nature landscape"
User request: "trip to Patagonia last month"
Refined:      "Dramatic Patagonia mountain landscape, snow-capped peaks under stormy clouds, vast open wilderness"

Slot default: "athlete in action"
User request: "basketball highlight from last game"
Refined:      "Basketball player driving to the hoop, explosive movement, crowd in background blurred"

Adding a New Composition

See references/composition-guide.md to add a new Remotion composition to the registry.

Safety and Fallback

Network & credential scope

  • All credentials stay local. SHOTAI_TOKEN is sent only to the local ShotAI MCP server (127.0.0.1). LLM API keys (if configured) are sent only to their respective provider endpoints — never to ShotAI, YouTube, or any other service.
  • The clip file server binds to 127.0.0.1 only (default port 8080). It is not accessible from other machines on the network. It serves temporary clip files to the Remotion renderer running on the same machine and shuts down after rendering completes.
  • yt-dlp is optional. Use --bgm /path/to/local.mp3 to skip all YouTube network access. When yt-dlp is used, it only downloads a single background music track — no other data is sent to YouTube.
  • LLM access is optional. Set AGENT_PROVIDER=none to run in heuristic mode with zero external network calls (aside from the local ShotAI MCP server).

Error handling

  • If SHOTAI_URL or SHOTAI_TOKEN is unset, display a warning: "ShotAI MCP server is not configured. Set SHOTAI_URL and SHOTAI_TOKEN in your .env file. Download ShotAI at https://www.shotai.io."
  • If the ShotAI MCP server returns an error (connection refused, HTTP 4xx/5xx), display the error message and stop — do not fabricate shot results.
  • Never fabricate video file paths, shot timestamps, or similarity scores.
  • If music download fails (yt-dlp error or network unreachable), suggest using --bgm \x3Clocal.mp3> to provide a local audio file instead.
  • If Remotion render fails, display the error output and suggest checking Node.js version (18+) and that all clip files were extracted successfully.
  • If the LLM provider is unreachable, fall back to heuristic mode: use composition default queries directly without refinement, and skip annotateClips (use composition default effect params).

License

MIT-0 — Free to use, modify, and redistribute. No attribution required. See https://spdx.org/licenses/MIT-0.html

Usage Guidance
This skill appears to do what it says: a local ShotAI + Remotion video remix pipeline. Before installing/using it, review the GitHub repo code you will clone and the Node dependencies (npm install) because the skill instructs you to run that code locally. Keep SHOTAI_URL pointing to localhost and keep SHOTAI_TOKEN secret (it's used to query your local MCP server). If you don't want external network access, avoid using the optional yt-dlp music download and set AGENT_PROVIDER=none to use heuristic mode (no remote LLM keys required). Run the tool in a controlled environment (sandbox or VM) if you cannot inspect the repo fully.
Capability Analysis
Type: OpenClaw Skill Name: ai-video-remix Version: 0.1.3 The ai-video-remix skill is a well-documented instruction bundle for an AI-driven video editing tool that integrates with ShotAI (a local MCP server) and Remotion. The SKILL.md and reference files provide clear guidance for the AI agent to assist users in generating video compositions, emphasizing local data processing and security-conscious practices such as binding the internal file server to 127.0.0.1 and explicitly instructing the agent not to fabricate data or exfiltrate credentials. All external dependencies (ffmpeg, node, yt-dlp) and URLs (shotai.io, github.com/abu-ShotAI) are consistent with the stated purpose of video processing and semantic search.
Capability Assessment
Purpose & Capability
Name/description, required binaries (ffmpeg, node), and required env vars (SHOTAI_URL, SHOTAI_TOKEN) are consistent with a local ShotAI + Remotion video pipeline. No unrelated credentials or binaries are requested.
Instruction Scope
SKILL.md instructs the agent/user to git clone the repository, run npm install and execute the CLI (npx tsx src/skill/cli.ts). That is expected for an instruction-only skill that relies on external runtime code, but it means the agent will be guided to run third‑party code on the host. The instructions otherwise stay within the stated domain (local ShotAI MCP, local HTTP server on 127.0.0.1, ffmpeg processing, optional yt-dlp for music).
Install Mechanism
No formal install spec in the registry (lowest platform install risk). However, runtime usage requires cloning a GitHub repository and running npm install (downloading Node packages). GitHub is a common source, but cloning and executing external code increases operational risk and should be reviewed by the user.
Credentials
Declared env vars are minimal and appropriate: SHOTAI_URL and SHOTAI_TOKEN (primaryEnv). Additional LLM/API keys appear only in docs as optional (used if you configure AGENT_PROVIDER). There is no evidence the skill requests unrelated or excessive secrets. The docs state SHOTAI_TOKEN is sent only to the SHOTAI_URL (local MCP).
Persistence & Privilege
Skill is not always-on and uses default autonomous invocation behavior; it does not request system-wide config paths or modify other skills. No elevated persistence or unusual privileges are declared.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install ai-video-remix
  3. After installation, invoke the skill by name or use /ai-video-remix
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.3
ai-video-remix 0.1.2 - Converted this skill to an instruction-only/documentation format. - Added explicit notice that runtime source code must be cloned separately; no code is bundled. - Provided GitHub source and homepage links in metadata. - Updated Quick Start instructions to clarify cloning and setup process. - No code or functional changes included in this release.
v0.1.1
ai-video-remix 0.1.1 - Added initial release files: README.md and package.json - Clarified that only videos imported and indexed in ShotAI collections are searchable; local files alone will not work - Specified all search/processing is localhost-only and ShotAI MCP server is required - Updated documentation to emphasize local processing and environment variable requirements - Added Openclaw-compatible metadata for binary and environment configuration
v0.1.0
ai-video-remix 0.1.0 - Initial release of the AI-driven video remix generator. - Generates styled video compositions from a user's local ShotAI video library using natural language requests. - Integrates semantic search (ShotAI), LLM-based planning, and Remotion rendering for personalized highlight reels, vlogs, sports montages, and more. - Supports both standard and probe modes for flexible shot selection based on user library content. - Includes comprehensive CLI options, troubleshooting guidance, and quality tuning recommendations. - Provides clear safety and fallback mechanisms for missing dependencies or API failures.
Metadata
Slug ai-video-remix
Version 0.1.3
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 3
Frequently Asked Questions

What is Ai Video Remix?

AI-driven video remix generator that uses ShotAI semantic search + LLM planning + Remotion rendering to produce styled video compositions from a user's local... It is an AI Agent Skill for Claude Code / OpenClaw, with 221 downloads so far.

How do I install Ai Video Remix?

Run "/install ai-video-remix" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Ai Video Remix free?

Yes, Ai Video Remix is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Ai Video Remix support?

Ai Video Remix is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Ai Video Remix?

It is built and maintained by Yoki (@abu-shotai); the current version is v0.1.3.

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