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What this makes

A faceless explainer: arbitrary text — an article, notes, a topic, a brief — becomes a narrated video where every visual is invented per scene (typography, abstract graphics, diagrams, data-viz). The /faceless-explainer workflow picks a design system, reshapes your text into a teaching story, generates its own TTS narration, and builds it frame by frame. Faceless means there’s nothing to capture. No site, no footage, no asset inventory — the visuals are designed downstream. If you have a product to sell use /product-launch-video; if you have a real site to show use /website-to-video; a GitHub PR goes to /pr-to-video. Unsure → start at /hyperframes.

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Base prompt

Verified, from the examples page — a ~60-second vertical explainer from pasted text:
/faceless-explainer Turn this into a ~60-second 1080x1920 vertical explainer: [paste your text]. One idea per scene, big typography, diagrams over stock footage, brand color #FF5533 on off-black. Male TTS voice, calm. Embedded captions, keywords highlighted in the brand color.
Rendered from the prompt above, unedited. Note the ~ — with a supplied script the runtime follows the spoken words, so ask for about a minute, not exactly one. See the anatomy for the rest of the skeleton.

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Variants

/faceless-explainer Make a ~30-second 1920x1080 explainer on how HTTPS keeps a request private, for a non-technical audience — the takeaway: your data is sealed before it leaves the browser. Concept angle: one idea per scene, big geometric type, a simple lock-and-key diagram as the centerpiece (swap the metaphor with the topic). Near-black ink on off-white with a deep-blue accent. Female TTS voice, warm and clear. Embedded captions, key terms highlighted in the accent color.
Shorter runtime, landscape for YouTube / embed. Fewer scenes means the topic has to compress — naming the takeaway tells the workflow what to keep.Rendered from this prompt with the topic swapped to HTTP caching (cache diagram as the metaphor), unedited — 26s, because the narration sets the length.
/faceless-explainer Make a ~45-second 1080x1920 listicle: “5 habits of fast-shipping teams”. Listicle angle — one habit per scene, each with a big number and a one-line label, escalating energy toward #1. Off-black with a lime accent. Male TTS voice, upbeat. Embedded captions, the habit label highlighted each scene.
The listicle angle gives each item its own scene with a consistent number-and-label shape, so the structure reads as a countdown rather than a wall of points.
/faceless-explainer Make a ~60-second 1920x1080 how-to on setting up a CI pipeline, for developers. How-to angle: one step per scene, each built around a simple node-and-arrow diagram that draws on as the narration explains it. Charcoal with a teal accent. Calm male TTS voice. Embedded captions, the step name highlighted.
A how-to leans on diagrams as the load-bearing visual. Describe the diagram shape per step (“node-and-arrow”, “a pipeline that fills left to right”) and let the workflow invent the specifics.

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The knobs that matter

KnobWhat to sayWhy it matters
Verbatim vs summarized”use my wording verbatim” or “restructure it freely”The workflow asks once. Verbatim keeps your voice but locks the word count; summarized lets it cut and reorder for pace
Duration”~60 seconds”, never “60 seconds”With a script the narration sets the real length; a hard number forces the agent to trim or pad the words
Scene density”one idea per scene”A faceless scene has one invented focal to animate; two ideas in a scene leave nothing to build the motion around, and it reads as a text dump
Angle”concept” / “how-to” / “listicle” / “narrative”The angle decides the story shape — the workflow reshapes your text into it rather than reading paragraphs in order
Caption style”embedded captions, keywords highlighted in the accent color”Captions are burned in; naming the highlight color ties them to the palette instead of a default pill
Palette”brand color #FF5533 on off-black”With no site to borrow from, the preset supplies a full palette; a named accent + ground personalizes it
Voice”male TTS voice, calm” / “warm female voice”Gender and tone are prompt words; the provider is a workflow decision
The single biggest quality lever here is scene density. “One idea per scene” turns a dense paragraph into a paced sequence — the workflow reorders and compresses your text to hit it, which is exactly what makes an explainer teach instead of recite.

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Common failure modes

“60 seconds” instead of “~60 seconds”. A supplied script’s spoken duration is not knowable until the TTS renders; a hard target makes the agent mangle the words to hit the clock.
  • ❌ a 60-second explainer from this text: ...
  • ✅ a ~60-second explainer from this text: ...
Cramming ideas into a scene. Every faceless visual is invented around a single focal; overload the scene and there’s no clear thing to animate.
  • ❌ explain all five caching layers in one scene
  • ✅ one idea per scene — one caching layer at a time
Asking it to capture or pull real imagery. There is no capture step; a faceless explainer invents its visuals.
  • ❌ pull screenshots from the site and explain the feature
  • ✅ that’s a site or product video — use /website-to-video or /product-launch-video
Leaving the look unspecified when you care. With no brand to read, the preset picks the palette; if you have colors, name them.
  • ❌ make it look on-brand
  • ✅ brand color #FF5533 on off-black