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Higgsfield Faceless Video

Higgsfield AIOfficialPublished by Higgsfield AI

  • Skill
  • Content generator
  • Design and creative
  • MIT
  • Low risk
  • Has scripts

From the author

Create a finished faceless explainer, documentary, illustrated story or children's music video, or edit a previously created faceless video. Use when: "make a faceless video", "create a narrated explainer", "make a children's song video", "edit this faceless video". NOT for: a single silent clip, ads or UGC, unrelated footage edits, or script-only requests.
— the description by Higgsfield AI

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The higgsfield-faceless-video skill provides a structured process for creating finished faceless video content. It supports various formats such as illustrated explainers, documentaries, illustrated stories, and children's music videos. The skill manages the end-to-end production workflow, including script validation, voice selection, asset management, and final assembly of video and audio blocks. It also provides capabilities for editing previously generated videos and adding subtitles.

What it does

  • Generates finished faceless videos based on user-provided topics and scripts.
  • Supports multiple production modes including illustrated explainers, channel-style motion, and children's songs.
  • Validates scripts against duration requirements and timing gates before generation.
  • Manages voice selection and dialogue generation using specified presets.
  • Assembles video and audio blocks into a final output file.
  • Adds subtitles to videos using local transcription models.

When to use it

  • When you need to create a narrated explainer or documentary video.
  • When you want to produce a children's song video with consistent visuals.
  • When you need to edit or update a previously generated faceless video.
  • When you require a video with a specific visual style and structured narration.

Advantages

  • Ensures consistent visual identity across video blocks.
  • Provides tools to verify script timing and narration duration before incurring costs.
  • Supports specific production modes for different content types like diagrams or stories.
  • Enables precise assembly of video and audio pairs without altering speech speed.

Usage examples

“make a faceless video about the history of the steam engine”
The agent will initiate the production workflow to create a documentary-style video, including script validation and asset generation.
“make a children's song video about counting apples”
The agent will use the song production mode to generate a synchronized music video based on the provided topic.
“edit this faceless video to change the narration in the second block”
The agent will use the editing workflow to update the specified block while preserving the rest of the video's production state.
“create a narrated explainer about photosynthesis”
The agent will generate an illustrated explainer video using diagram-led scenes and narration.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/higgsfield-ai/higgsfield-faceless-video/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip higgsfield-faceless-video.zip -d .agents/skills

Documentation by Higgsfield AI

Faceless video

Create one finished video with a consistent visual style and narration. For an illustrated explainer use deliberate, diagram-led scenes; for a story or documentary adapt the pacing and visuals to the brief. Do not treat an explainer as a request for rapid cuts. Preserve choices and assets supplied by the user.

Choose the requested mode before generating: illustrated explainers use references/production.md; fast-cut channel motion uses references/channel-motion.md; stills and picture stories use references/picture-story.md; a sung children's music video uses references/song.md; explicitly requested talking characters use references/talking-characters.md; a requested presenter overlay uses references/presenter.md alongside the motion workflow; edits to a previously generated video use references/editing.md. A request for background music alone is not a song request. Never infer a presenter from an incidental photo.

When the brief supplies animation_mode, treat fully_animated as motion and scene_based as stills without asking again. Resolve song intent from the complete brief, including topic and script; an explicitly sung children's video uses song mode even when a voice is supplied. Preserve the production mode when continuing or editing an existing video.

Before spending credits

Resolve missing topic, approximate duration, aspect ratio, language, visual style, voice, music and subtitle choices. Never invent a preset or voice ID. Use higgsfield preset list video-explainer --json and higgsfield voices list --json for current choices, and resolve a selected preset with higgsfield preset resolve video-explainer <id> --json. Confirm photo roles before using reference images. Honor the requested duration; never silently round it up.

Find this skill's installed directory and retain its absolute path as SKILL_DIR. Keep all work in a persistent session directory, not the skill directory. Before generation verify higgsfield account status, ffmpeg, ffprobe, python3, curl, and awk, and inspect the live schemas using higgsfield model get for each planned model. Estimate generation costs with higgsfield generate cost where supported; if an estimate is unavailable, disclose that before generation. If any required stage, model, dependency, or requested feature is unavailable, explain and stop before paid work. Do not call explainer_video or video_explainer.

Read references/production.md for the generation, assembly, QC, recovery and delivery procedure. For subtitles, read references/captions.md and check its dependencies before paid generation. Read references/creative.md for style, assets, long-form planning and review, references/styles.md for style guidance, and references/prompts.md when writing the scene plan. The executable helper scripts/assemble_blocks.sh assembles ordered video/audio pairs without changing speech speed; read its usage before running it. The previous skill name is supported for existing installations.

Files

references/production.md

Production workflow

  1. For factual topics, research reliable sources and retain a short source list. For personal stories, use supplied facts. Plan one illustrated scene and one narration line per 10-second block; use a shorter final block when the requested duration is not a multiple of 10. Avoid cutting a sentence. For a final visual-only tail of at most three seconds, create silent audio and use --last-visual-only.

  2. Create a style key with a supported image model. For a selected preset, resolve it via the CLI and follow the returned media contract. Reuse the style and any selected character consistently. Preserve the user's chosen aspect ratio. Check a first rendered clip before submitting the rest; inspect each result for visual and identity drift.

  3. Select one voice and keep the exact voice_id and voice_type pair. For a full 10-second block, start with approximately 26–30 spoken words in one flowing line and use a consistent delivery cue and a nine-second time window, for example [voice: warm, clear, lively conversational delivery, starts speaking immediately] [00:00-00:09] <spoken line>. Keep the cue out of the authored caption text. This is a starting point, not proof of timing or wording: inspect the generated take and adjust its text for the selected voice and language. For a shorter final block, plan to its actual window. Inspect the current seed_audio schema, then use higgsfield generate create seed_audio --prompt "<line>" --voice-id <id> --voice-type <type> --wait --json. Download each completed take and, before generating video, run bash "$SKILL_DIR/scripts/check_voice.sh" voice01.wav 10 (use the actual shorter window for a short final block). Each spoken take must end within [window−2.0, window−0.2] seconds; rewrite and regenerate a failing line, never speed up the audio. Allow at most three attempts per line, then report the timing failure without claiming a completed result. Keep each job ID, result URL, and block number as soon as returned.

  4. Inspect the current minimax_h3 schema. Submit a 10-second background for each block with the chosen aspect ratio and style reference when supported; pass the completed style image's job ID directly when the media parameter supports it. Wait for terminal results. Use the returned job output URL, never construct one. Generate speech separately and exclude spoken words from background prompts. Respect the live model schema rather than passing unavailable flags.

  5. Download completed clips and voices to the working directory using ordered names such as clip01.mp4 and voice01.wav. Confirm every file is nonempty and decodable. Assemble in order, for example:

bash "$SKILL_DIR/scripts/assemble_blocks.sh" --out final.mp4 \
  --last-seconds 5 clip01.mp4 voice01.wav clip02.mp4 voice02.wav

The example makes a 15-second video. Omit --last-seconds for full blocks. The script validates speech timing, duration, audio and decoding and writes an assembly receipt. For a requested music bed, inspect sonilo_music, generate one instrumental track with higgsfield generate create sonilo_music --duration 40 --prompt "<music description>" --wait --json, download it and pass it via --music; omit it when music is declined. If a gate fails, correct the input and rerun; do not bypass it or return loose clips as a completed video. Review the final video and audio for content, sync, framing and visual continuity. 6. If captions were requested, follow references/captions.md, inspect their timing and legibility, then use the captioned file as the deliverable. 7. To provide a hosted result when requested, run higgsfield upload create final.mp4 --json and use the returned confirmed URL; otherwise deliver the local file if the host supports it. Report actual duration, aspect, language, subtitle status and sources.

Resume from saved completed outputs. Poll running jobs with higgsfield generate wait <job_id> --json; do not submit duplicates while a job is running. Respect generation failures and refusals.

Requirements and compatibility

Written for: Claude Code

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Claude Code frontmatter, Needs Python

Security

What our scanner noticed· Low risk

  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

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Attribution and licence

Published by
Higgsfield AI
Publisher
Higgsfield AI (Official)
Source
higgsfield-ai/skills · higgsfield-faceless-video · commit 2700040
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download higgsfield-faceless-video.zip