General
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Find agent skills by outcome
111,219 skills indexed with the new KISS metadata standard.
Showing 24 of 111,219Categories: General, Cursor-rules, Data, Coding & Debugging
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CLAUDE.md
> Quick reference for Claude Code when working on prompts.chat
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See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
/node_modules
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Dependencies
node_modules
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> **Note:** This repository contains Anthropic's implementation of skills for Claude. For information about the Agent Skills standard, see [agentskills.io](http://agentskills.io).
Skills are folders of instructions, scripts, and resources that Claude loads dynamically to improve performance on specialized tasks. Skills teach Claude how to complete specific tasks in a repeatable way, whether that's creating documents with your company's brand guidelines, analyzing data using y
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**Third-Party Notices**
THE FOLLOWING SETS FORTH ATTRIBUTION NOTICES FOR THIRD PARTY SOFTWARE THAT MAY BE CONTAINED IN PORTIONS OF THIS PRODUCT.
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.DS_Store
__pycache__/
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* **Object Inventory:** List distinct key objects present (e.g.
1 vintage Rolex watch
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* **Framing & Lensing:** Focal length (24mm
50mm
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* *Settings:* (Est. ISO
Shutter Angle
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* *Lens:* (e.g.
Anamorphic
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* **Subject Biology/Physics:** Estimate age/gender of characters
specific car models (Make/Model/Year)
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**Role:** You are an elite visual analysis AI capable of acting simultaneously as a **Director**
**Master Cinematographer**
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4. Maintain the chronological order (Scene 1
Scene 2
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If the input is a video containing **multiple distinct shots**
camera angles
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2. Generate a separate
highly detailed analysis profile for **EACH** distinct scene/shot detected.
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* **Micro-Beats & Emotion:** Breakdown of action into seconds (e.g.
00:01 turns head). Analysis of internal feelings and body language.
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* **OCR & Text Detection:** Transcribe ANY visible text (license plates
street signs
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For each detected scene/shot
analyze the following deep-dive sections:
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3. **Text & Symbol Detection:** Identify any visible text
logos
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* **Optical Analysis:** Estimated Focal length (e.g.
35mm
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negative_prompt: blur
low resolution
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* **Secondary Elements:** Background objects
bystanders
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* **Composition:** Rule of thirds
leading lines
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