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video-generation

video-generation

github.com/hyperfx-aiCreative & media107210 installsUpdated 4d ago
Repository

About video-generation

A Hyper MCP skill for generating, analyzing and editing videos with AI models and FFmpeg-backed tools. It covers production from generation through subtitles, audio, clips and quality review.

Key features

  1. 01Generate video from text or image prompts
  2. 02Analyze video content and quality
  3. 03Capture frames and transcribe audio
  4. 04Generate and burn subtitles
  5. 05Create voiceovers and manage audio tracks
  6. 06Extract, stitch and overlay clips

Use cases

  1. 01Generate and review a video before delivery
  2. 02Add subtitles, voiceover or titles to a video
  3. 03Turn long videos into shorter clips

MCP support

Exposes Hyper MCP video, audio and editing tools to an agent, including generation, analysis, transcription, subtitles and post-production. Provider integrations must be configured in Hyper.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/hyperfx-ai/marketing-skills --skill video-generation

After installing, type/video-generationin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
generation.md
post-production.md
ugc-video.md
video-prompting.md
workflows.md

Details

From the project README

Video Generation & Editing

Guide for generating, editing, analyzing, and post-processing videos using AI models and FFmpeg-backed tools exposed through the Hyper MCP.

Requirements

This skill assumes the Hyper MCP is connected to your agent so the tools below are available. The underlying providers (Google Veo, ByteDance Seedance, OpenAI TTS, transcription, etc.) are configured under your Hyper integrations.

How to run the tools in this skill

Every tool in this skill is named by its canonical tool name. Run it with the call your surface gives you:

SurfaceFind a toolRun it
MCP client (Claude, Cursor, Codex, ChatGPT)search("<what you want to do>"), then describe("<name>")call("<name>", {...})
Hyper CLIhyperai search "<what you want to do>", then hyperai describe <name>hyperai call <name> --json '{...}'

If a tool is not found, its integration is not connected or not enabled for the workspace: stop and tell the user which integration to connect.

Tool surface

GroupTools
Generationvideos_generate
Analysisvideos_analyze, videos_frames_capture, videos_transcribe
Subtitles & captionsvideos_subtitles_generate, videos_subtitles_burn, videos_captions_burn_highlighted
Audioaudio_speech_generate, videos_audio_add
Editingvideos_clips_extract, videos_stitch, videos_text_overlays_add

Out of scope

  • Image generation, ad creative composition, brand extraction — use image-generation or ad-creative-generation.
  • Posting finished videos to social platforms — use tiktok, instagram, or linkedin.
  • Running paid video campaigns — use google-ads, meta-ads, tiktok-ads.

Available Tools

ToolPurposeRuns in Background
videos_generateGenerate video from text / image promptYes
videos_frames_captureExtract frame as imageNo
videos_analyzeWatch and understand video contentNo
videos_transcribeExtract audio transcriptNo
videos_subtitles_generateCreate SRT / VTT subtitle fileNo
videos_subtitles_burnBurn subtitles onto videoYes
videos_captions_burn_highlightedTikTok / karaoke-style word-by-word captionsYes
audio_speech_generateGenerate voiceover audio from textNo
videos_audio_addAdd / replace audio track on videoYes
videos_clips_extractExtract a time segment from videoYes
videos_stitchConcatenate multiple clipsYes
videos_text_overlays_addAdd text / titles to videoYes

Video Understanding

You can watch and analyze any video using videos_analyze. This sends the video to a multimodal AI that sees both visual and audio content.

When to use videos_analyze
  • After generating a video: check if it matches your intent
  • Before stitching: verify scene consistency across clips
  • Quality review: check for glitches, character drift, lighting issues
  • Content understanding: "what happens in this video?"
Analysis Types
videos_analyze(file_id="...", analysis_type="general")
videos_analyze(file_id="...", analysis_type="quality_review")
videos_analyze(file_id="...", analysis_type="scene_breakdown")
videos_analyze(file_id="...", question="Does this match: [original prompt]?")
Self-Review Workflow

Always review generated videos before delivering to the user:

result = videos_generate(prompt="...", model="veo-3.1-generate-preview")
review = videos_analyze(file_id="video_file_id", analysis_type="quality_review")
# If issues found, regenerate with adjustments. If quality is good, proceed to editing.

Routing table

All reference files live in references/. Read them at references/<file> (e.g. references/generation.md).

The user wants to…Read these files first
Generate a video (any model)references/generation.md — model selection, parameter matrix, prompt templates
Build a longer multi-scene videoreferences/generation.md — script planning + scene chaining
Add subtitles / captions / voiceover / overlays, or clip a videoreferences/post-production.md
Produce UGC / TikTok content end-to-endreferences/ugc-video.md (ugc_videos_create modes) → references/workflows.md
Shape a prompt for a specific model (Veo / Seedance / Kling)references/video-prompting.md
Turn a podcast / long video into short clipsreferences/workflows.md → references/post-production.md
Understand or QA an existing videoUse videos_analyze (see Video Understanding above)

Best Practices

  1. Review before delivering: always use videos_analyze to check your output.
  2. Maintain visual consistency: use the same character descriptions, lighting, and style across all scenes.
  3. Plan transitions: design the end of each scene to flow into the next.
  4. Batch similar scenes: generate scenes with similar settings together.
  5. Review before chaining: check each scene before using its last frame for the next.
  6. Use single-variable iteration: remix / regenerate by changing one variable at a time.
  7. Add captions for accessibility: use the subtitle pipeline for all UGC content.

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