Agent skill · Audited from source

higgsfield-video-explainer

skill · higgsfield-ai/skillsMIT licenceAudited 26 Oct 2026 · source d60a8ba7e89c

★ 1,669pushed 30 days agoversion 0.13.0
✓SAFEGrade B · 89/100 · 26 Oct 2026 · d60a8ba
1,669repo stars · whole higgsfield-ai/skills

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit d60a8ba7e89c and found no filesystem, network or shell access and no hard-coded secrets. What it does: Build a complete non-photoreal narrated explainer or story video from ordered 10-second blocks: one narrator, one universal style key, one Seed Audio take and one Gemini Omni clip per block, then server-side assembly…

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Cite this page

ModelsAtlas. “higgsfield-video-explainer (higgsfield-ai/skills)”. Retrieved 26 Oct 2026. https://modelsatlas.com/skills/higgsfield-ai/higgsfield-video-explainer

Trust audit

Audit 0.4.1 · source read 26 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low1 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS1
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (1)

INFOSupply chainprompt.pipe_to_shell · SKILL.md:45
F-08 Supply chainCWE-829 · CWE-1357Layer L2
curl -fsSL https://raw.githubusercontent.com/higgsfield-ai/cli/main/install.sh | sh
Why
No further detail recorded for this rule.
Fix
—

Audit 0.4.1 · source sha d60a8ba7e89c · 26 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publisherhiggsfield-ai GitHub organizationOwner of the repository this skill is read from
  • Source folderhiggsfield-ai/skills/higgsfield-video-explainerThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdictd60a8ba7e89cA new audit runs when the source changes
  • Repository statusNot archivedLast push 30 days ago
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Build a complete non-photoreal narrated explainer or story video from ordered 10-second blocks: one narrator, one universal style key, one Seed Audio take and one Gemini Omni clip per block, then server-side assembly…

---
version: 0.13.0
name: higgsfield-video-explainer
description: |
  Build a complete non-photoreal narrated explainer or story video from
  ordered 10-second blocks: one narrator, one universal style key, one Seed
  Audio take and one Gemini Omni clip per block, then server-side assembly
  with explainer_video. Use when: "make an explainer video", "explain this in
  a video", "turn this topic or document into a narrated video", "tell this
  story as an animated video", "make a faceless narrated video", or "show me
  explainer styles". Supports live CMS presets, custom style references,
  mascot/faceless modes, two aspects, and optional burned subtitles. NOT for:
  photoreal films, ads/UGC, talking heads, podcasts, motion typography reels,
  one-off clips without narration, or editing a finished video.
argument-hint: "[topic or source files] [duration] [language] [aspect ratio]"
allowed-tools: Bash
---

# 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 operation | CLI equivalent |
|---|---|
| `get_explainer_presets` | `higgsfield preset list video-explainer --json` |
| `resolve_explainer_preset` | `higgsfield preset resolve video-explainer <preset_id> --json` |
| `generate_image` / `nano_banana_pro` | `higgsfield generate create nano_banana_2 ...` |
| `list_voices` | `higgsfield voices list --json` |
| `generate_audio` / `seed_audio` | `higgsfield generate create seed_audio ...` |
| `generate_video` / `gemini_omni` | `higgsfield generate create gemini_omni ...` |
| `job_status` | `--wait --json` or `higgsfield generate wait <job_id> --json` |
| `explainer_video` | `higgsfield 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:

   ```bash
   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:

   ```bash
   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:

```bash
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

| Phase | Output | CLI |
|---|---|---|
| 0 Ask | style first; then duration, language, character, aspect, subtitles | `preset list` + user questions |
| R Research | verified facts and sources | available research tools |
| 1 Style key | one universal style image | `preset resolve` or `nano_banana_2` |
| 2 Narration | N labeled narration lines | reasoning |
| 3 Block prompts | N labeled video prompts | reasoning |
| 4 Voice | user selects one voice; generate N takes | `voices list` + `seed_audio` |
| 5 Clips | generate N 10-second clips | `gemini_omni` |
| 6 Assemble | one final MP4 | `explainer_video` |

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

## Phase R — research

For a real to

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit d60a8ba

Download folder ↗
git clone https://github.com/higgsfield-ai/skills
git -C skills checkout d60a8ba7e89c

The author documents no install command, so this uses the repository directly. Our verdict covers commit d60a8ba7e89c only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source d60a8ba7e89c

README badge

For maintainers · shows the latest audit

ModelsAtlas: SAFE BMODELSATLASSAFE · B
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Questions about higgsfield-video-explainer

Is higgsfield-video-explainer safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can higgsfield-video-explainer access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (d60a8ba7e89c), read on 2026-10-26. The repository is watched, and a new audit runs when it changes — this is the first audit.

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