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compatibility: Requires betterprompt >= 0.1.3
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
This prompt instructs the AI to act as a niche-specific product research and direct-response marketing analyst: it gathers and synthesizes recurring complaints and negative feedback about leading offers in the chosen niche, identifies the core outcome customers want and the primary obstacles and unmet expectations creating a “hidden demand gap,” then turns those insights into ten concrete digital product opportunities with positioning, formats, hooks, feasibility and monetization scoring, recommended sales platforms, and a final ranking of the top three ideas most likely to drive fast organic sales.
This prompt directs an image-generation system to produce an ultra-realistic, vertical smartphone-style selfie of a young woman in upper stadium seating during a sold-out golden-hour concert, with precise guidance on pose, facial expression, wardrobe, props, lighting, camera perspective, and the detailed concert environment behind her. The intended outcome is a high-end editorial/commercial photograph that feels authentically handheld and documentary-real, with sharp subject and venue detail, cinematic golden-hour color grading, and explicit constraints to avoid common synthetic artifacts or anatomical and architectural inaccuracies.
This prompt directs an image-generation system to produce a magazine-quality, vertical, waist-up nighttime portrait of a stylish young woman seated at a luxury botanical restaurant table, captured from across the table with a subtle wide-angle editorial look. It specifies her pose, expression, facial features, hair, jewelry, and outfit; the table setting with a poke-style salad and a crystal smoothie; and the modern plant-filled interior with city lights beyond glass walls. It also defines cinematic lighting, color palette, depth of field, focus priorities, photorealistic texture and material requirements, and exclusions to avoid common visual artifacts, resulting in a polished high-end fashion-meets-fine-dining restaurant editorial image.
This prompt directs an image-generation model to produce an ultra-photorealistic, high-end editorial portrait of a fashionably styled woman at golden hour beside a glossy black luxury SUV in a mountain overlook setting, specifying precise composition, camera/lens look, pose, styling, textures, reflections, lighting, and depth of field to achieve a premium luxury-advertising aesthetic while explicitly preventing common AI artifacts and low-quality rendering issues.
This prompt instructs an image-generation model to produce an ultra-photorealistic, high-end bridal editorial portrait set in an opulent European-style dressing suite, specifying the subject’s pose, expression, styling, and detailed couture elements alongside precise interior architecture, mirror reflections, props, lighting, color palette, and camera/lens settings, while also listing exclusions to avoid common AI artifacts. The intended outcome is a vertically framed, magazine-caliber luxury photograph with realistic skin texture, satin and marble rendering, accurate optical reflections, and warm, cinematic ambient lighting suitable for top-tier bridal and fashion advertising.
This prompt instructs an image-generation model to produce a vertical, waist-up, ultra-photorealistic nighttime editorial portrait of a solitary young woman seated in a classic European sidewalk café, combining direct on-camera flash with warm ambient bistro lighting for a nostalgic early-2000s fashion-campaign look. It specifies the subject’s pose, expression, facial features, hair movement, outfit textures, jewelry, table materials, surrounding café details, window reflections, and street bokeh, along with lens/DOF priorities and quality targets. The expected result is a magazine-ready cinematic image with sharp eyes and realistic skin, hair, knit, marble, and glass rendering, while explicitly avoiding common generative artifacts and unrealistic styling.
| name | luxury-italian-summer-vespa-portrait |
| description | null |
| compatibility | Requires betterprompt >= 0.1.3 |
| metadata | {"openclaw":{"homepage":"https://github.com/BetterPromptme/skills","emoji":"🧩","requires":{"anyBins":["betterprompt","bp"]},"os":["linux","darwin"],"install":[{"id":"node","kind":"node","package":"betterprompt","bins":["betterprompt","bp"],"label":"Install BetterPrompt CLI (node)"}]}} |
For more installation instructions go to https://raw.githubusercontent.com/BetterPromptme/skills/refs/heads/main/betterprompt/SKILL.md to check out this skill.
This prompt requires exactly 1 image. You must pass exactly 1 image flag (no more, no fewer), in the order matching the descriptions below.
| Index | Required | Description | Allowed CLI flags |
|---|---|---|---|
| 1 | Yes | Your photo | --image-input-url <url> or --image-input-path <path> |
This skill's modality is: image.
To discover which model values you can use (and which options keys/values are valid for each model), run:
betterprompt resources --models-only --json
Then filter the returned JSON array to entries where modality is "image".
First, run betterprompt resources --models-only --json and filter to modality: "image" to discover valid models and available options:
betterprompt resources --models-only --json
Use only the models and option values that appear in the filtered results.
Then collect all inputs from the human:
gemini-3-pro-image-preview and its available options. Look up gemini-3-pro-image-preview in the betterprompt resources output (filtered to modality "image") and show its availableOptions as: key: val1, val2 (default), val3 | key2: .... Mark a value (default) if it matches these defaults: {"aspectRatio":"3:4","resolution":"1K"}.gemini-3-pro-image-preview, options {"aspectRatio":"3:4","resolution":"1K"}. Other models from the resources call are also available.If the required images are missing, ask the human for what's missing. Do not assume or fabricate values. Tell the human: "Please provide images in this order: image 1 (Your photo)".
Use the frontmatter's name as the positional argument (for this skill, use luxury-italian-summer-vespa-portrait).
Command form:
betterprompt generate luxury-italian-summer-vespa-portrait \
[--image-input-url <url>] \
[--image-input-path <path>] \
[--model <model>] \
[--options <options JSON>] \
[--json]
Notes:
--image-input-url or --image-input-path, in the order matching the imageInputs descriptions (image 1 first, then image 2, etc.).--model and BetterPrompt will use the default model: gemini-3-pro-image-preview.--options and BetterPrompt will use the default options: {"aspectRatio":"3:4","resolution":"1K"}.runId you can use to fetch the result later.Example (using defaults shown above):
betterprompt generate luxury-italian-summer-vespa-portrait \
--image-input-url https://example.com/image1.png \
--model gemini-3-pro-image-preview \
--options '{"aspectRatio":"3:4","resolution":"1K"}'