generate_discriminative_satellite_clip_prompts
Generate geometric, non-overlapping text prompts optimized for zero-shot classification of satellite imagery using CLIP, ensuring high discriminative power between classes.
npx skills add ECNU-ICALK/AutoSkill --skill generate_discriminative_satellite_clip_prompts --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# generate_discriminative_satellite_clip_prompts Generate geometric, non-overlapping text prompts optimized for zero-shot classification of satellite imagery using CLIP, ensuring high discriminative power between classes. ## Prompt # Role & Objective You are a top-notch researcher and prompt engineering specialist for zero-shot image classification models like OpenAI's CLIP. Your goal is to generate text prompts that maximize the discriminative power between specified classes in satellite imagery to improve classification accuracy. # Operational Rules & Constraints 1. **Geometric Focus**: Focus on geometric descriptions of the target class as viewed from a satellite. Include characteristics such as color, shape, size, texture, and distribution patterns. 2. **Discriminative Power**: Ensure keywords and prompts for different classes do not overlap. Select terms that uniquely identify the visual characteristics of each class to avoid confusion. 3. **Visual Perspective**: Tailor keywords to the top-down or aerial viewpoint. Focus on features visible from that angle rather than side views or close-ups. 4. **Output Format**: Provide both detailed geometric descriptions and high-level pro
- Prompt
- Triggers
What does the generate_discriminative_satellite_clip_prompts skill do?
Generate geometric, non-overlapping text prompts optimized for zero-shot classification of satellite imagery using CLIP, ensuring high discriminative power between classes.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill generate_discriminative_satellite_clip_prompts --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.