Connect a set of questions with the people they are meant to help. Numbered question strips build on the left; a single highlighted figure appears on the right, followed by a field of audience icons and a closing label. This seven-second animation illustrates a move from one person to a wider audience without claiming to measure its size.
What you get
A local generator, editable effect implementation and motion/review instructions. Generate a 1920×1080 HyperFrames composition and render it at 30 fps as a segment for your own edit.
Up to five editable questions and an audienceLabel. Ruled strips with square indexes establish the questions before attention shifts to the audience field.
A highlighted lead figure, question accent and fixed field of 24 line-art figures. Question rows begin at 0.20 seconds; the lead appears at 2.80 seconds, the field builds from 3.20 seconds and the label arrives at 4.80 seconds.
Four palettes preserve the same sequence: White & Yellow (white-yellow), Charcoal & Lime (charcoal-lime), Paper & Orange (paper-orange) and Black & White (midnight-ice). Semantic overrides can adapt the treatment; check contrast after changes. Dark palettes retain a fine static grid. Bundled local fonts include Inter, IBM Plex Mono for measurements and ordinals, Smiley Sans and Noto Sans SC. Chinese copy automatically uses Smiley Sans, including Latin text in the same composition; use --zh-font noto-sans-sc for the plainer face or --font for your supplied font. Recheck text bounds after a font change.
Before you choose
Choose this to explain an audience-oriented way of thinking. If you need to report real survey results, use a data visualization with explicit sample size and measures rather than a fixed illustrative crowd.
Good fit
A creator explaining how questions about one person can guide thinking about an audience.
A short lesson on user needs, interview preparation or a comparable topic where five concise questions form the visual argument.
A series using consistent question-list typography, audience imagery and motion across examples.
Not for
Audience analytics, a measured sample visualization or automatic demographic research. The 24-person field is fixed illustrative geometry, not a count derived from data.
A long questionnaire or dense survey results; the current composition displays five questions and one closing label.
Automatic editing of an entire film, generation of a presenter performance or soundtrack, or copying a reference creator’s identity and footage.
How to use
You say/creatormotion-cards-list-audience Turn my supplied explanation into a white-yellow B-roll scene using the Question List to Audience effect. Use the text, data and media I provide, and ask for any required input that is missing.
Write up to five questions and an audienceLabel in JSON. The sample asks who the audience is, what they want, what obstructs them, what they tried and what would help; use the questions appropriate to your actual explanation.
Decide what the move from one figure to many means. Use the label or narration to make it clear that the repeated icons represent an audience concept, not 24 interview participants or a verified growth result.
Keep each question concise enough for one compact strip and the label readable beneath the audience field. This effect uses line-art geometry, not active image slots or presenter footage; no avatar photos or alpha matte are needed.
Prepare Node.js 22+, FFmpeg and the documented HyperFrames CLI 0.8.30. From the extracted package run node scripts/create.mjs --out PROJECT --data CONTENT.json. Choose --style and optional semantic --overrides; --images replaces named local slots with paths relative to the image-map JSON. Unlisted slots retain their defaults. Read the image policy before adapting visual materials.
Inspect the editable project and render with npx --yes hyperframes@0.8.30 render PROJECT --output VIDEO.mp4 --fps 30 --quality high --strict. Review the rendered opening, every main change and final reading hold for clipping, contrast and overlap. Narration, music and assembly with other scenes remain separate production work. Check the question numbers during their clipped entrances and read the audience label after the field has finished appearing. Confirm that the visuals do not imply unsupported statistics.
Requirements and costs
You bring
questions: provide your own content or retain the illustrative default. · audienceLabel: provide your own content or retain the illustrative default.
Dependencies
HyperFrames CLI 0.8.30 or compatible — required · Node.js 22 or newer — required · FFmpeg — required
Outside costs
Not collected yet
Tools used
HyperFrames
Publisher testing
v1.0.1 — Claude Code / Claude Desktop / Cowork / Codex / ChatGPT
FAQ
Yes. Supply questions and audienceLabel in JSON, then choose a palette or semantic overrides. The visible question limit is five; additional entries do not add rows.
No. The current composition uses editable text and line-art people, without active presenter or raster-image slots. Generic footage and image-replacement instructions concern other effects that use those materials.
Yes. Preserve the question-list build, single-person focus and later audience expansion. Revealing only a list would remove the second visual mechanism that gives this effect its purpose.
Not through the current content controls. The code creates a fixed field of 24 people plus the highlighted lead figure. A data-linked count requires a deliberate implementation change and an explanation of what the icons represent.
The closing label should connect the questions to the audience idea. Read it with the narration and avoid presenting repeated icons as evidence that a claim applies to a measured population.
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