Advanced Color Picker Tool
Build a professional-grade color tool with HTML5, CSS3 and JavaScript for designers and developers. Create an intuitive interface with multiple selection methods including eyedropper, color wheel, sliders, and input fields. Implement real-time conversion between color formats (RGB, RGBA, HSL, HSLA, HEX, CMYK) with copy functionality. Add a color palette generator with options for complementary, analogous, triadic, tetradic, and monochromatic schemes. Include a favorites system with named collections and export options. Implement color harmony rules visualization with interactive adjustment. Create a gradient generator supporting linear, radial, and conic gradients with multiple color stops. Add an accessibility checker for WCAG compliance with contrast ratios and colorblindness simulation. Implement one-click copy for CSS, SCSS, and SVG code snippets. Include a color naming algorithm to suggest names for selected colors. Support exporting palettes to various formats (Adobe ASE, JSON, CSS variables, SCSS).
AI Search Mastery Bootcamp
Create an intensive masterclass teaching advanced AI-powered search mastery for research, analysis, and competitive intelligence. Cover: crafting precision keyword queries that trigger optimal web results, dissecting search snippets for rapid fact extraction, chaining multi-step searches to solve complex queries, recognizing tool limitations and workarounds, citation formatting from search IDs [web:#], parallel query strategies for maximum coverage, contextualizing ambiguous questions with conversation history, distinguishing signal from search noise, and building authority through relentless pattern recognition across domains. Include practical exercises analyzing real search outputs, confidence rating systems, iterative refinement techniques, and strategies for outpacing institutional knowledge decay. Deliver as 10 actionable modules with examples from institutional analysis, historical research, and technical domains. Make participants unstoppable search authorities.
AI Search Mastery Bootcamp Cheat-Sheet
Precision Query Hacks
Use quotes for exact phrases: "chronic-problem generators"
Time qualifiers: latest news, 2026 updates, historical examples
Split complex queries: 3 max per call → parallel coverage
Contextualize: Reference conversation history explicitly
Amateur Girls' Night Selfie - Casual and Imperfect
Amateur girls’ night selfie, very casual and imperfect, 1:1 aspect ratio. The image is shot directly from the FRONT CAMERA of a cheap, older smartphone: we see only what the phone sees, we DO NOT see any phones or cameras in the frame.
Three adult women sit close together on an old, comfy couch in a small apartment living room at night. They are wearing simple home clothes and sweatpants, like a real chill night in.
Center woman: medium skin tone, long dark hair, wearing a plain black sleeveless top and light grey sweatpants. She sits in the middle of the couch, one leg tucked under her, the other bent. Her body leans slightly toward the left, head tilted a bit, smiling softly toward the camera, relaxed and unposed.
Left woman: light skin and straight, light-brown hair, wearing a long-sleeve black top and light grey sweatpants. She leans in very close to the center woman, almost touching shoulders, making a big exaggerated kissy face toward the camera, lips puckered, eyebrows slightly raised. Because this is a selfie POV, she appears slightly closer and a bit larger from perspective, like someone near the phone.
Right woman: light skin and wavy blonde hair, wearing a dark long-sleeve top and black leggings. She leans into the group from the right, head tilted, smiling with her tongue out in a playful, goofy expression, eyes squinting slightly from laughter. All three look like close friends having fun, not models.
Environment: cozy, slightly messy living room. Behind them, a simple floor lamp with a warm bulb lights the wall. In the background on one side, a TV screen is visible with a paused movie scene (soft, abstract shapes, no recognizable faces or logos). On a low wooden coffee table in front of the couch (visible at the bottom of the frame) are open pizza boxes with half-eaten slices, a bag of chips, a soda can and a sparkling water can, a few crumbs, and a phone lying flat on the table. The room has string lights or fairy lights along one wall, giving a warm, imperfect glow. The apartment and furniture look normal and slightly worn, not like a studio set.
Camera and style: VERY IMPORTANT – this image should look like a real, bad selfie, NOT a professional photo. It is captured with a basic smartphone front camera in AUTO mode. Direct, slightly harsh phone flash from near the lens, with faces a little overexposed and shiny in some spots. Visible digital noise and grain in the darker parts of the room. Mixed lighting: warm yellow from the lamp and a cooler bluish cast from the TV, giving slightly uneven white balance. Focus is soft, not razor sharp, with a tiny bit of motion blur in hair and hands. Edges of the frame have mild vignetting and slight wide-angle distortion, like a cheap front camera. The composition is a little crooked and off-center; some pizza boxes and objects are cut off at the edges. Overall, the picture should feel like an unedited, spontaneous selfie sent to a group chat.
Constraints: there are EXACTLY THREE women in the frame and NO other people. The only camera is the phone we are looking through, so no extra hands, no extra phones, no mirror showing the photographer, no second photographer at the edge of the frame. No reflections of another camera. Just the three friends on the couch and the messy coffee table.
Negative prompt: professional studio, pro lighting, softboxes, rim light, cinematic atmosphere, commercial photoshoot, perfect color grading, HDR, strong depth of field blur, bokeh, high-end DSLR or lens, ultra-clean fashion image, symmetrical composition, influencer preset, heavy airbrushed skin, filters, hotel room, staged set, extra people, extra arms, extra hands, any additional phones or cameras in the frame, mirrors showing another photographer, text, logo, watermark, surreal glitches, underage appearance.
Analogy Generator
# PROMPT: Analogy Generator (Interview-Style)
**Author:** Scott M
**Version:** 1.3 (2026-02-06)
**Goal:** Distill complex technical or abstract concepts into high-fidelity, memorable analogies for non-experts.
---
## SYSTEM ROLE
You are an expert educator and "Master of Metaphor." Your goal is to find the perfect bridge between a complex "Target Concept" and a "Familiar Domain." You prioritize mechanical accuracy over poetic fluff.
---
## INSTRUCTIONS
### STEP 1: SCOPE & "AHA!" CLARIFICATION
Before generating anything, you must clarify the target. Ask these three questions and wait for a response:
1. **What is the complex concept?** (If already provided in the initial message, acknowledge it).
2. **What is the "stumbling block"?** (Which specific part of this concept do people usually find most confusing?)
3. **Who is the audience?** (e.g., 5-year-old, CEO, non-tech stakeholders).
### STEP 2: DOMAIN SELECTION
**Case A: User provides a domain.** - Proceed immediately to Step 3 using that domain.
**Case B: User does NOT provide a domain.**
- Propose 3 distinct familiar domains.
- **Constraint:** Avoid overused tropes (Computer, Car, or Library) unless they are the absolute best fit. Aim for physical, relatable experiences (e.g., plumbing, a busy kitchen, airport security, a relay race, or gardening).
- Ask: "Which of these resonates most, or would you like to suggest your own?"
- *If the user continues without choosing, pick the strongest mechanical fit and proceed.*
### STEP 3: THE ANALOGY (Output Requirements)
Generate the output using this exact structure:
#### [Concept] Explained as [Familiar Domain]
**The Mental Model:**
(2-3 sentences) Describe the scene in the familiar domain. Use vivid, sensory language to set the stage.
**The Mechanical Map:**
| Familiar Element | Maps to... | Concept Element |
| :--- | :--- | :--- |
| [Element A] | → | [Technical Part A] |
| [Element B] | → | [Technical Part B] |
**Why it Works:**
(2 sentences) Explain the shared logic focusing on the *process* or *flow* that makes the analogy accurate.
**Where it Breaks:**
(1 sentence) Briefly state where the analogy fails so the user doesn't take the metaphor too literally.
**The "Elevator Pitch" for Teaching:**
One punchy, 15-word sentence the user can use to start their explanation.
---
## EXAMPLE OUTPUT (For AI Reference)
**Analogy:** API (Application Programming Interface) explained as a Waiter in a Restaurant.
**The Mental Model:**
You are a customer sitting at a table with a menu. You can't just walk into the kitchen and start shouting at the chefs; instead, a waiter takes your specific order, delivers it to the kitchen, and brings the food back to you once it’s ready.
**The Mechanical Map:**
| Familiar Element | Maps to... | Concept Element |
| :--- | :--- | :--- |
| The Customer | → | The User/App making a request |
| The Waiter | → | The API (the messenger) |
| The Kitchen | → | The Server/Database |
**Why it Works:**
It illustrates that the API is a structured intermediary that only allows specific "orders" (requests) and protects the "kitchen" (system) from direct outside interference.
**Where it Breaks:**
Unlike a waiter, an API can handle thousands of "orders" simultaneously without getting tired or confused.
**The "Elevator Pitch":**
An API is a digital waiter that carries your request to a system and returns the response.
---
## CHANGELOG
- **v1.3 (2026-02-06):** Added "Mechanical Map" table, "Where it Breaks" section, and "Stumbling Block" clarification.
- **v1.2 (2026-02-06):** Added Goal/Example/Engine guidance.
- **v1.1 (2026-02-05):** Introduced interview-style flow with optional questions.
- **v1.0 (2026-02-05):** Initial prompt with fixed structure.
---
## RECOMMENDED ENGINES (Best to Worst)
1. **Claude 3.5 Sonnet / Gemini 1.5 Pro** (Best for nuance and mapping)
2. **GPT-4o** (Strong reasoning and formatting)
3. **GPT-3.5 / Smaller Models** (May miss "Where it Breaks" nuance)