higgsfield-video-explainer

작성자: higgsfield-ai

순서가 지정된 10초 블록으로 완전한 비사진적 내레이션 설명 영상 또는 스토리 영상을 제작합니다: 블록마다 내레이터 1명, 범용 스타일 키 1개, Seed Audio 테이크 1개, Gemini Omni 클립 1개를 사용한 후 explainer_video로 서버 측에서 조합합니다. 다음 경우에 사용: "설명 영상 만들어 줘", "이걸 영상으로 설명해 줘", "이 주제나 문서를 내레이션 영상으로 바꿔 줘", "이 이야기를 애니메이션 영상으로 들려줘", "얼굴 없는 내레이션 영상 만들어 줘", 또는 "설명 스타일 보여줘". 라이브 CMS 프리셋, 맞춤 설정을 지원합니다...

npx skills add https://github.com/higgsfield-ai/skills --skill higgsfield-video-explainer

Higgsfield Video Explainer

Run the MCP video-explainer workflow through Higgsfield CLI. Lock one visual style key, write one narration line and one matching visual prompt per 10-second block, generate every voice take first, generate every clip second, then immediately assemble the ordered pairs with explainer_video.

Never use the monolithic video_explainer job in this skill.

MCP-to-CLI mapping

MCP workflow operationCLI equivalent
get_explainer_presetshiggsfield preset list video-explainer --json
resolve_explainer_presethiggsfield preset resolve video-explainer <preset_id> --json
generate_image / nano_banana_prohiggsfield generate create nano_banana_2 ...
list_voiceshiggsfield voices list --json
generate_audio / seed_audiohiggsfield generate create seed_audio ...
generate_video / gemini_omnihiggsfield generate create gemini_omni ...
job_status--wait --json or higgsfield generate wait <job_id> --json
explainer_videohiggsfield generate create explainer_video ...

nano_banana_2 is the public CLI id for the Nano Banana Pro style-key model used by the MCP workflow.

Bootstrap

  1. If higgsfield is unavailable, install it:

    curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh
    
  2. If higgsfield account status fails, ask the user to run higgsfield auth login, then wait.

  3. Inspect the live contracts before the first submission:

    higgsfield model get nano_banana_2
    higgsfield model get seed_audio
    higgsfield model get gemini_omni
    higgsfield model get explainer_video
    

Phase 0 — ask first

Collect choices in two separate turns, in this order. Never merge them.

Turn 1 — style only

Always load the live CMS catalog:

higgsfield preset list video-explainer --json

Show the preset names with their thumbnail/video preview URLs. Say one short line asking the user to pick a preset, describe a custom style, or attach style-reference images, then end the turn. Do not ask production questions in the same turn. Choosing a style is mandatory; never choose silently unless the user explicitly says “you choose.”

Skip this turn only when the request already contains explainer preset id: <uuid>. Confirm that UUID exists in the live catalog and keep it for Phase 1.

Turn 2 — production settings

Only after style selection, collect every unresolved setting:

  • Duration: one to ten whole minutes. N = duration_minutes × 6 fixed 10-second blocks.
  • Narration language: English by default, but still offer the choice.
  • Character: recurring mascot or faceless stylistic scenes. Always ask.
  • Aspect: 16:9 by default or 9:16 vertical.
  • Subtitles: off by default. Explain that subtitles cost 0.05 credit per voiced block. If enabled, make the user choose patrick, caveat, marker, or anton; never choose silently.

Every choice belongs to the user unless they explicitly delegate it.

Inputs

  • Topic or personal/philosophical story.
  • Optional local source documents; read/extract them before scripting. They are factual input, not generation media.
  • Optional preset UUID, mutually exclusive with custom style-reference images.
  • Optional style-reference images. Use only their rendering style and color grading; never copy their people, text, logos, or objects unless requested.
  • Duration, language, character mode, aspect, and subtitle choice from Phase 0.

For local style donors, pass each path with a repeated --image. For a web image, download it locally first or use an existing uploaded media ID.

Hard rules

  • Keep every visual strictly non-photorealistic. Repeat the same STYLE descriptor and non-realism negatives in every clip prompt.
  • Keep all spoken words out of video generation. Clip audio is ambient sound or music only; no dialogue, lip-sync, or baked narration.
  • Use exactly one narration take and one clip per labeled block. Block N audio always maps to Block N video.
  • Attach the same style-key image to every clip.
  • Write all image/video prompts in English. Only narration uses the selected language.
  • Research real topics before scripting. Do not invent quotes, dates, numbers, or events.
  • Assemble automatically in the same run. Returning loose clips is a failure.

Pipeline

PhaseOutputCLI
0 Askstyle first; then duration, language, character, aspect, subtitlespreset list + user questions
R Researchverified facts and sourcesavailable research tools
1 Style keyone universal style imagepreset resolve or nano_banana_2
2 NarrationN labeled narration linesreasoning
3 Block promptsN labeled video promptsreasoning
4 Voiceuser selects one voice; generate N takesvoices list + seed_audio
5 Clipsgenerate N 10-second clipsgemini_omni
6 Assembleone final MP4explainer_video

Read references/prompts.md before Phases 1–3.

Phase R — research

For a real topic, use available web research tools and authoritative sources to verify enough facts for every block. Keep a short Sources list. Never script a factual explainer from memory alone.

For a personal story, skip web research and use only details supplied by the user. Invent nothing factual.

Phase 1 — create or resolve the style key

Write one reusable STYLE descriptor: medium, palette, line/fill behavior, texture/finish, then non-photorealistic, illustrated, not a photo, no live-action, no realism.

Selected CMS preset

Resolve the hidden style image into the active workspace:

higgsfield preset resolve video-explainer "<preset UUID>" --json

Keep the returned media_id as STYLE_KEY_ID. Skip image generation: this imported media is the style key. Build the STYLE descriptor from the returned preset name plus the mandatory non-photoreal rules. Do not recreate a preset from its name.

The preset reference controls framing. If it conflicts with the aspect requested in Phase 0, stop and let the user choose rather than silently fighting the reference.

Custom style or reference images

Generate exactly one key image. Use the abstract swatch template from references/prompts.md, or its mascot variant when character mode is enabled. Repeat --image for every style donor:

higgsfield generate create nano_banana_2 \
  --prompt "<style-key prompt>" \
  --aspect_ratio 16:9 \
  --resolution 2k \
  --wait \
  --json

Use 9:16 for vertical. Keep the completed image job UUID as STYLE_KEY_ID; later CLI generations can reuse a completed job UUID as an image reference.

Phase 2 — write narration

Write exactly N labeled narration blocks in the selected language:

Block 1
<line spoken over clip 1>
Block 2
<line spoken over clip 2>
  • One line per block, usually 20–24 words and about 8–9 seconds.
  • Keep every take under roughly 9.5 seconds.
  • Use plain spoken text only: no timecodes, emotion cues, parentheticals, or stage directions.
  • Spell numbers out.
  • Use a concrete tone and never say “in this video.”
  • For a topic, build from hook through payoff. For a personal story, preserve the user's details and protagonist.

Phase 3 — write matching video prompts

Write exactly N labeled English prompts using the template in references/prompts.md:

Block N
STYLE REFERENCE: Match the attached reference image EXACTLY. <same STYLE descriptor>
SCENE: <one scene and action matching Block N narration>
MOTION: <camera move and animation behavior>
AUDIO: <ambient SFX or music only; no voice, dialogue, or narration>
NEGATIVE: <style drift and realism bans; no lip-sync, captions, text, logos, or watermark>

For mascot mode, Block 1 greets by gesture with mouth closed, the final block waves a sign-off, and middle blocks use consistent cameos only when useful. For faceless mode, use stylistic scenes only. Keep one clear action per block.

Phase 4 — generate every voice take first

List the live voices, present the choices, and wait for the user to select one narrator:

higgsfield voices list --json

Keep the selected voice's exact id and type (preset or element). Never invent or auto-pick a voice unless the user explicitly delegates it.

Generate one completed seed_audio job per narration block, always with the same voice:

higgsfield generate create seed_audio \
  --prompt "<Block N narration only>" \
  --voice_type "<preset|element>" \
  --voice_id "<voice UUID>" \
  --wait \
  --json

Record every audio job UUID in block order. Regenerate only a failed or excessively long take. Shorten that block or adjust --speech_rate modestly when needed. Do not begin Phase 5 until all N audio jobs are complete.

Phase 5 — generate every clip second

Generate one completed 10-second gemini_omni clip per block. Attach the same style key to every call:

higgsfield generate create gemini_omni \
  --prompt "<Block N video prompt>" \
  --image "<STYLE_KEY_ID>" \
  --duration 10 \
  --resolution 720p \
  --aspect_ratio 16:9 \
  --wait \
  --json

Use 9:16 when selected. Record every video job UUID in block order. Independent jobs may run concurrently inside this phase, but the audio-phase barrier is strict. Re-submit only failed blocks. Never silently replace gemini_omni; inspect the live video catalog if the model is unavailable.

Phase 6 — assemble immediately

Create blocks.json with at least two ordered block pairs. The CLI model contract requires typed references, so use the generic completed-job types:

[
  {
    "video": {"id": "<clip 1 job UUID>", "type": "video_job"},
    "audio": {"id": "<voice 1 job UUID>", "type": "audio_job"}
  },
  {
    "video": {"id": "<clip 2 job UUID>", "type": "video_job"},
    "audio": {"id": "<voice 2 job UUID>", "type": "audio_job"}
  }
]

Submit the server-side assembler immediately:

higgsfield generate create explainer_video \
  --items @blocks.json \
  --width 1280 \
  --height 720 \
  --wait \
  --json

Use --width 720 --height 1280 for vertical. When subtitles are enabled, add the chosen font:

--subtitles '{"font":"patrick"}'

The assembler keeps each block at exactly 10 seconds: it centers short voice takes, pitch-safely speeds small overruns, never stretches video, concatenates blocks in order, and optionally burns timed captions. Total duration is exactly N × 10 seconds.

Do not use local ffmpeg, the legacy assembly scripts, or the monolithic video_explainer job.

Checkpoints and recovery

  • Before Phase 5: require one style key, exactly N narration lines and prompts, one selected voice, and N completed audio jobs.
  • Before Phase 6: require N completed video jobs and exact one-to-one block pairing with no missing or duplicate IDs.
  • Preset missing: refresh preset list; never reuse or fabricate an ID.
  • Preset resolve failure: verify workspace selection and retry once.
  • Style drift or realism: strengthen the shared STYLE and NEGATIVE text, then regenerate only that clip.
  • Timeout: rejoin with higgsfield generate wait <job_id> --json; never duplicate a running job.
  • Two identical failures mean the prompt or parameters must change.

Deliver

Return the final assembled video URL, exact duration, aspect, narration language, selected style, narrator, subtitle status, and a Sources list for researched topics. Keep intermediate job IDs and loose asset URLs internal unless requested.

higgsfield-ai의 다른 스킬

higgsfield-marketplace-cards
higgsfield-ai
Higgsfield를 통해 마켓플레이스 제품 이미지 카드를 생성합니다: 규격에 맞는 메인 이미지, 보조 제품 이미지, A+ 스타일 콘텐츠 모듈. 사용자가 마켓플레이스 리스팅 이미지, 제품 상세 카드, 보조 제품 이미지, 제품 인포그래픽, 라이프스타일 리스팅 샷, A+ 스타일 콘텐츠, 마켓플레이스 이미지 세트, 또는 판매 준비된 제품 비주얼을 요청할 때 사용합니다. 백엔드가 마켓플레이스 규정 준수 참조 및 프롬프트 템플릿을 소유하며, 이 스킬은 사용자 의도를 CLI로 라우팅만 합니다. 일반적인 용도가 아닙니다...
creativemarketingdesign
higgsfield-soul-id
higgsfield-ai
소울 캐릭터를 훈련합니다. 이는 힉스필드가 신원을 충실히 반영한 이미지 및 비디오 생성을 위해 사용하는, 사람의 얼굴에 기반한 개인화된 모델입니다. 다음 경우에 사용: "내
creativemediavideo
higgsfield-brandkit
higgsfield-ai
Higgsfield CLI와 번들된 결정적 로컬 도구를 통해 완전한 시각적 브랜드 시스템을 생성하고 확장합니다: 팔레트, SVG 로고 마크, 타이포그래피, 목업, 소셜 그래픽, 패키징, 간판, 포스터, 프레젠테이션 덱, 편집 가능한 PPTX/PDF 브랜드북. 공식 제공 자산을 보존하고, 승인을 로컬에 유지하며, 종속된 출력물만 재생성합니다. 사용 시점: "브랜드 키트 만들기", "비주얼 아이덴티티 제작", "로고 및 브랜드북 디자인", "이 로고를 브랜드에 적용...
higgsfield-product-photoshoot
higgsfield-ai
Higgsfield product-photoshoot 프롬프트 강화를 통해 GPT Image 2 / gpt_image_2에서 브랜드 수준의 제품 이미지를 생성합니다. 전문 브랜드/제품 비주얼을 위한 진입점입니다. 사용 시점: "제품 사진", "스튜디오 촬영", "라이프스타일 이미지", "핀터레스트 핀", "히어로/배너", "캐러셀", "광고 크리에이티브", "메타 광고", "가상 피팅", "모델 착용", "제품을 든 사람", "손 클로즈업", "공중 부양/떠다니는/튀는 제품", "CGI/초현실적 제품", "스타일 변경", "계절/미적 변형",...
creativemarketingdesign
higgsfield-generate
higgsfield-ai
Higgsfield AI를 통해 이미지/비디오를 생성합니다. 기본값: 이미지/디자인/텍스트용 GPT Image 2, 비디오용 Seedance 2.0, 캐릭터/참조 이미지 작업용 Nano Banana 2/Pro, 아바타/제품/훅/설정이 포함된 광고용 Marketing Studio, Soul V2/Cinema/Cast/Location 및 Kling 3.0. 사용 시점: "이미지 생성", "비디오 만들기", "이 사진 애니메이션화", "이미지-투-비디오", "이 이미지 편집/스타일 변경/리믹스", "클립 제작", "광고 만들기", "UGC 비디오 제작", "제품 데모", "언박싱", "브랜드 비디오"...
creativemediavideo
higgsfield-websites
higgsfield-ai
Build, edit, and deploy full-stack websites via the Higgsfield CLI (`higgsfield website …`). Each site is a React 19 + TanStack Start SSR app in one Cloudflare Worker (D1/R2/KV/DO/Containers). TWO product types, picked via `--type` on create: `website` (standalone, NO Higgsfield integration, independent brand, custom CSS — the image-grounded pipeline in references/website-flow.md) vs `app` (Sign in with Higgsfield + fnf SDK, Quanta + app layouts per references/app-flow.md). This file routes...
developmentapi
higgsfield-youtube-thumbnail
higgsfield-ai
Higgsfield CLI를 통해 높은 클릭률의 YouTube 썸네일과 세로형 비디오 커버를 제작합니다. 진실된 정보 격차 개념을 구축하고, 최대 3개의 참조된 정체성을 보존하며, 로고와 통제된 변형을 지원하고, Nano Banana Pro로 메인 이미지를 렌더링하며, 집중된 Seedream 편집을 적용합니다. 사용 시점: "YouTube 썸네일 만들기", "이 비디오의 썸네일", "MrBeast 스타일 커버", "Shorts 커버", 또는 "Instagram 비디오 커버". 진실된 주제가 확정된 후 모든 비디오 워크플로우 뒤에 연결하세요...