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

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

Video Understanding

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

When to use analyze_video

• 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

analyze_video(file_id="...", analysis_type="general")
analyze_video(file_id="...", analysis_type="quality_review")
analyze_video(file_id="...", analysis_type="scene_breakdown")
analyze_video(file_id="...", question="Does this match: [original prompt]?")

Self-Review Workflow

Always review generated videos before delivering to the user:

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

Script Planning

For longer, cohesive videos, plan the FULL SCRIPT before generating:

1. Scene Breakdown

• Scenes: break story into segments
  • Sora: 4 / 8 / 12 seconds per scene
  • Veo: 4-8 seconds per scene
  • Seedance: 4-15 seconds per scene (native audio with lip-sync)
• Camera: shot type (wide, close-up, tracking), angles, movement
• Transitions: how each scene connects to the next
• Consistency: character descriptions, color palette, visual style

Scene Chaining Technique

To create seamless multi-scene videos:

Scene 1 (text-to-video)

generate_video(prompt="...", model="veo-3.1-generate-preview")

Scene 2+ (image-to-video)

capture_video_frame(video_file_id="scene1_file_id", frame_position="last")
generate_video(prompt="continuation: ...", image_file_id="captured_frame_id")

Repeat: extract last frame → generate next scene.

Stitching Scenes Together

After generating all scenes, combine them:

stitch_videos(video_file_ids=["scene1_id", "scene2_id", "scene3_id"])

stitch_videos(
    video_file_ids=["scene1_id", "scene2_id", "scene3_id"],
    transition="crossfade",
    crossfade_duration=0.5,
)

Subtitle / Caption Workflow

Full pipeline: Video → Transcript → Subtitles → Burned Video

transcript = transcribe_video(file_id="video_file_id")

subs = generate_subtitles(file_id="video_file_id", transcript=transcript, format="srt")

burn_subtitles(
    video_file_id="video_file_id",
    subtitle_file_id=subs.file_id,
    style="bold_outline",
    position="bottom",
)

Subtitle Styles

Text Overlays

Add titles, lower-thirds, CTAs, and other graphics:

overlay_text(
    video_file_id="video_file_id",
    overlays=[
        {
            "text": "Episode 1: The Beginning",
            "start_time": 0.0,
            "end_time": 3.0,
            "position": "center",
            "font_size": 48,
            "color": "white",
            "background": "black@0.5",
        },
        {
            "text": "Subscribe for more!",
            "start_time": 10.0,
            "end_time": 14.0,
            "position": "bottom-right",
            "font_size": 28,
        },
    ],
)

Overlay Positions

top, bottom, center, top-left, top-right, bottom-left, bottom-right

Voiceover / Narration

Generate natural-sounding voiceover with TTS and add it to any video:

audio = text_to_speech(
    text="Welcome to our product. Here's how it works...",
    voice="nova",
    model="tts-1",
)

add_audio_to_video(
    video_file_id="video_id",
    audio_file_id=audio.file_id,
    mode="replace",
)

add_audio_to_video(
    video_file_id="video_id",
    audio_file_id=audio.file_id,
    mode="mix",
    audio_volume=0.8,
)

Available Voices

alloy, ash, coral, echo, fable, nova (recommended), onyx, sage, shimmer

Highlighted Captions (TikTok / Reels Style)

Add word-by-word highlighted captions that light up as spoken:

burn_highlighted_captions(
    video_file_id="video_id",
    style="tiktok",
    highlight_color="#3B82F6",
    base_color="white",
    words_per_group=3,
    position="center",
)

burn_highlighted_captions(
    video_file_id="video_id",
    style="karaoke",
    highlight_color="yellow",
    base_color="white",
    background="black@0.6",
    words_per_group=4,
    position="bottom",
)

Video Clipping

Extract segments from longer videos:

clip_video(
    video_file_id="long_video_id",
    start_time=45.0,
    end_time=60.0,
)

UGC / TikTok Production Workflow

Complete workflow for producing UGC-style content:

1. Script: plan scenes, dialogue, and visual style
2. Generate: create each scene with generate_video
3. Review: use analyze_video to check each scene for quality
4. Chain: extract last frames with capture_video_frame, generate next scenes
5. Stitch: combine all scenes with stitch_videos
6. Narrate: generate voiceover with text_to_speech + add_audio_to_video
7. Caption: add TikTok-style captions with burn_highlighted_captions
8. Overlay: add titles / CTAs with overlay_text
9. Final review: use analyze_video on the final video for quality check

Example: Narrated UGC Video

generate_video(prompt="...", model="veo-3.1-generate-preview")

audio = text_to_speech(text="Your narration script here...", voice="nova")

add_audio_to_video(video_file_id="generated_video_id", audio_file_id=audio.file_id)

bur