hyperfx-ai/marketing-skills

video-generation

End-to-end AI video production through the Hyper MCP — text-to-video and image-to-video generation (Sora, Veo, Seedance), scene chaining, video analysis, transcription, subtitles, TikTok / karaoke captions, voiceover (TTS), audio mixing, clipping, stitching…

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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 (OpenAI Sora, Google Veo, ByteDance Seedance, OpenAI TTS, transcription, etc.) are configured under your Hyper integrations.

Tool surface

GroupTools
Generationvideos_generate, sora_videos_remix, sora_videos_delete
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
sora_videos_remixModify existing Sora videoYes
sora_videos_deleteDelete a Sora videoNo
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

python
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:

python
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 (Sora / Veo / Seedance / Kling)references/video-prompting.md
Turn a podcast / long video into short clipsreferences/workflows.mdreferences/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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