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Ugc Video Prompts

Organization
palmier-io
ugc-video-prompts

Generate ultra-realistic UGC/influencer-style video clips inside Palmier Pro — talking selfies, product demos, candid lifestyle motion — using the proven still-then-animate pipeline instead of cold text-to-video. Drives Palmier Pro's generate_video, get_timeline, and get_media tools directly, with model selection grounded in this project's actual capabilities (dialogue/audio support, reference limits, resolution). Use whenever the user wants UGC-style video, influencer clips, talking-to-camera ad creative, "make a video of [a person/product]," or animating a still into motion — even if they don't say "UGC" explicitly. Pairs with the ugc-photo-prompts skill, which should run first to produce the anchor still.

Overview

Publisherpalmier-io
Repositorypalmier-skills
Skill nameugc-video-prompts
Stars
82
Forks
10
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by palmier-io on GitHub. Read the source before you install it.

Installation

Install the Ugc Video Prompts AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/palmier-io/palmier-skills/tree/main/skills/ugc-video-prompts
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/palmier-io/palmier-skills.git /tmp/palmier-skills
mkdir -p .claude/skills
cp -r /tmp/palmier-skills/skills/ugc-video-prompts .claude/skills/ugc-video-prompts
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ugc Video Prompts in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ugc Video Prompts on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ugc Video Prompts is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

UGC-Style Video Prompts

Core principle

Video models are decent at motion but worse than image models at solving "doesn't look AI" from zero — skin, lighting, and identity drift across many frames in ways a single still doesn't. Don't text-to-video a UGC clip from scratch. Generate the anchor still first (with the ugc-photo-prompts skill, or reuse one already in the media library), then animate it. The still already solved realism; the video model only has to solve movement and speech, which is what it's actually good at.

The pipeline

  1. Anchor still. Already exists in the media library, or generate one with ugc-photo-prompts. This locks subject identity, wardrobe, product, lighting, and skin texture before any motion is added.
  2. Motion prompt. Describe only what changes from that frame — camera behavior, body motion, speech. Don't redescribe the subject/setting; the still already carries that.
  3. Model pick. Based on whether the beat needs synced dialogue, multiple combined references, or just clean simple motion — see the table below.
  4. One clip = one beat. A full UGC ad is a sequence of short jump-cut beats (hook, demo, reaction, CTA), not one continuous shot. Generate each beat as its own clip off the same anchor (or a small consistent set of anchors), then cut them together on the timeline.
  5. Lock the voice across beats. Same problem as appearance drift, different mechanism — describe the voice explicitly in every beat's prompt (or pin it with a referenceAudioMediaRefs clip on Seedance) so the speaker doesn't sound like a different person from one cut to the next.

Motion-prompt formula

The still already did slots 1–4 and 6–8 from the photo formula. This is just what's added for motion:

  1. Seed reference. State plainly that this animates the provided still — most models infer this from startFrameMediaRef/referenceImageMediaRefs alone, but naming it keeps the prompt focused on change, not redescription.
  2. Camera behavior. Default to handheld micro-shake or a static phone propped on a surface — not a smooth gimbal move or a dolly/crane. "Smooth cinematic camera move" is as strong an AI tell in video as studio lighting is in stills.
  3. Subject motion. Small, continuous, natural movement — a weight shift, a blink, hair moving, a hand gesture mid-sentence. Avoid big choreographed actions unless the beat specifically calls for one (e.g., the demo beat).
  4. Speech, if any. Put the exact line in quotes, written the way someone actually talks — contractions, a small pause, not ad copy. "okay wait this actually smells amazing" reads as real; "Introducing our revolutionary new formula" doesn't, regardless of delivery. If this speaker appears in more than one beat, describe the voice itself — and always include all four: pitch, tone, accent, and pace, not just one or two. "A warm, slightly raspy voice" alone is incomplete; "a warm, friendly tone, medium-pitched, neutral American accent, relaxed conversational pace" is the actual bar. Reuse that exact wording verbatim in every beat's prompt — each generate_video call has no memory of any other, so the same anchor face will get a different voice per clip unless all four are pinned down explicitly every time. Seedance can do better than words: pass the rendered audio from beat one as a referenceAudioMediaRefs input on later beats to lock the actual voice rather than approximate it in text.
  5. Duration matched to the beat. Pick the shortest duration the model offers that fits one beat (often 4–6s) rather than padding a single clip to cover multiple actions — multi-action clips are where motion starts looking choreographed.
  6. Negative motion cues. Add: no smooth gimbal stabilization, no cinematic camera move, no professional production polish, no overly choreographed motion, no studio lighting. Carry over the standing negative list from ugc-photo-prompts for the visual frame itself.

Model selection

Grounded in this project's actual model catalog and observed behavior, including real failures — not just the catalog spec sheet.

Default to Grok Imagine Video or Kling V3 for most beats. Between those two: Kling for anything needing a longer or more nuanced line, Grok when a quick draft is enough.

ModelBest forNotes
Grok Imagine VideoDefault pick for most beatsRenders synced dialogue audio with accurate lip-sync in this project's tests. Caps at 720p — fine for most UGC use, not a 4k hero asset.
Kling V3 / Kling O3Default pick, especially longer/dialogue-heavy beatsRenders synced dialogue audio automatically when the prompt has a quoted line — confirmed repeatedly in this project. O3 allows more references (7 vs 3) if anchoring more than one element. Up to 4k, 3–15s, 16:9/9:16/1:1.
Seedance 2 / Seedance 2 MiniBeats combining multiple elements — person + product + a reference audio styleNever default to 1080p/4k on Seedance 2 — it's expensive. If a beat doesn't specifically need that resolution, use Seedance 2 Mini (720p cap) instead, and if full Seedance 2 at 1080p/4k seems warranted, tell the user it costs significantly more and let them opt in manually rather than generating it by default. Most flexible model otherwise: up to 9 image refs, 3 video refs, 3 audio refs, 12 total combined.
Veo 3.1 / Veo 3.1 FastAvoid as a default — use only if the user names it specificallyFails with a content-checker error often in this project (multiple failures across unrelated prompts/anchors in testing here) — unpredictable enough that it's not a safe default pick even though output quality is good when it works.

Hailuo 2.3 Pro and other catalog models are available but not part of the default rotation — only reach for them if the user asks by name.

Running this inside Palmier Pro

  1. Gate. get_timeline — if canGenerate is false, ask the user to sign in/subscribe. list_models({ type: "video" }) before every generate so model ids/caps match the live catalog. Propose model + duration + aspect + prompt; wait for confirmation (paid, not undoable).
  2. Get the anchor. get_media for an existing still; otherwise run ugc-photo-prompts first.
  3. Match the canvas. Use project width/height/fps for aspectRatio and beat duration.
  4. Generate. generate_video with startFrameMediaRef = anchor still (image-to-video). For Seedance multi-element beats use referenceImageMediaRefs / referenceAudioMediaRefs / referenceVideoMediaRefs and refer to them in the prompt as @Image1, @Audio1, etc. Apply the motion-prompt formula above. Optional folder: "UGC/Beats".
  5. Verify. Async — ready when get_media({ ids: [placeholder] }) has no generationStatus (absence = ready). On failed, report and ask before retry. Don't busy-poll.
  6. Assemble the beats.
    add_clips({
      entries: [
        { mediaRef: BEAT1, startFrame: 0 },
        { mediaRef: BEAT2, startFrame: END1 },   // or use insert_clips to ripple
      ]
    })
    Tighten with split_clips + ripple_delete_ranges / remove_words — there is no split_clip singular.
  7. Voiceover-only alternative. Pure b-roll + VO → generate_audio (TTS) instead of a dialogue video model.

Worked example

Continuing the skincare-serum still from ugc-photo-prompts: animate it on Kling V3 with a spoken hook line — "Starting from this image: she glances down at the bottle in her hand, then looks back up at the camera with a small grin and says, in a warm, friendly tone, mid-pitched voice, neutral American accent, relaxed conversational pace, 'okay wait, this actually smells amazing,' a slight handheld shake throughout, no cinematic camera move, no smooth gimbal, no studio lighting, no professional production polish." That's the hook beat. The demo beat (her actually applying it) and a CTA beat would each be separate, shorter clips off the same anchor — and the full voice description ("a warm, friendly tone, mid-pitched voice, neutral American accent, relaxed conversational pace") gets repeated verbatim in both, not just implied by reusing the same face.

Guardrails

  • Build fictional, generic personas — don't generate a specific real, identifiable person without their consent, and don't use this to recreate a named public figure's likeness.
  • Keep wardrobe/pose/action choices brand-safe and non-sexualizing by default; only go further if the user explicitly asks for it.

Frequently asked questions

What does the Ugc Video Prompts AI skill do?

Generate ultra-realistic UGC/influencer-style video clips inside Palmier Pro — talking selfies, product demos, candid lifestyle motion — using the proven still-then-animate pipeline instead of cold text-to-video. Drives Palmier Pro's generate_video, get_timeline, and get_media tools directly, with model selection grounded in this project's actual capabilities (dialogue/audio support, reference limits, resolution). Use whenever the user wants UGC-style video, influencer clips, talking-to-camera ad creative, "make a video of [a person/product]," or animating a still into motion — even if they...

Why use Ugc Video Prompts on TypingMind?

Because you install it once and use it with any model. Ugc Video Prompts is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ugc Video Prompts in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/palmier-io/palmier-skills/tree/main/skills/ugc-video-prompts. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ugc Video Prompts?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ugc Video Prompts?

As many as you like. As long as a model supports skills, you can use Ugc Video Prompts with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ugc Video Prompts AI skill free?

Yes. It is published on GitHub by palmier-io under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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