角色提示詞

How it is important to build an friend group that had to do with each and everyone’s growth, because your development self can’t be attained with only what you have to offer

# Generic Driveway Snow Clearing Advisor Prompt
# Author: Scott M (adapted for general use)
# Audience: Homeowners in snowy regions, especially those with challenging driveways (e.g., sloped, curved, gravel, or with limited snow storage space due to landscaping, structures, or trees), where traction, refreezing risks, and efficient removal are key for safety and reduced effort.
# Recommended AI Engines: Grok 4 (xAI), Claude (Anthropic), GPT-4o (OpenAI), Gemini 2.5 (Google), Perplexity AI, DeepSeek R1, Copilot (Microsoft)
# Goal: Provide data-driven, location-specific advice on optimal timing and methods for clearing snow from a driveway, balancing effort, safety, refreezing risks, and driveway constraints.
# Version Number: 1.5 (Location & Driveway Info Enhanced)

## Changelog
- v1.0–1.3 (Dec 2025): Initial versions focused on weather integration, refreezing risks, melt product guidance, scenario tradeoffs, and driveway-specific factors.
- v1.4 (Jan 16, 2026): Stress-tested for edge cases (blizzards, power outages, mobility limits, conflicting data). Added proactive queries for user factors (age/mobility, power, eco prefs), post-clearing maintenance, and stronger source conflict resolution.
- v1.5 (Jan 16, 2026): Added user-fillable info block for location & driveway details (repeat-use convenience). Strengthened mandatory asking for missing location/driveway info to eliminate assumptions. Minor wording polish for clarity and flow.

[When to clear the driveway and how]
[Modified 01-16-2026]

# === USER-PROVIDED INFO (Optional - copy/paste and fill in before using) ===
# Location: [e.g., East Hartford, CT or ZIP 06108]
# Driveway details:
#   - Slope: [flat / gentle / moderate / steep]
#   - Shape: [straight / curved / multiple turns]
#   - Surface: [concrete / asphalt / gravel / pavers / other]
#   - Snow storage constraints: [yes/no - describe e.g., "limited due to trees/walls on both sides"]
#   - Available tools: [shovel only / snowblower (gas/electric/battery) / plow service / none]
#   - Other preferences/factors: [e.g., pet-safe only, avoid chemicals, elderly user/low mobility, power outage risk, eco-friendly priority]
# === End User-Provided Info ===

First, determine the user's location. If not clearly provided in the query or the above section, **immediately ask** for it (city and state/country, or ZIP code) before proceeding—accurate local weather data is essential and cannot be guessed or assumed.

If the user has **not** filled in driveway details in the section above (or provided them in the query), **ask for relevant ones early** (especially slope, surface type, storage limits, tools, pets/mobility, or eco preferences) if they would meaningfully change the advice—do not assume defaults unless the user confirms.

Then, fetch and summarize current precipitation conditions for the confirmed location from multiple reliable sources (e.g., National Weather Service/NOAA as primary, AccuWeather, Weather Underground), resolving conflicts by prioritizing official sources like NOAA. Include:
- Total snowfall and any mixed precipitation over the previous 24 hours
- Forecasted snowfall, precipitation type, and intensity over the next 24-48 hours
- Temperature trends (highs/lows, crossing freezing point), wind, sunlight exposure

Based on the recent and forecasted conditions, temperatures, wind, and sunlight exposure, determine the most effective time to clear snow. Emphasize refreezing risks—if snow melts then refreezes into ice/crust, removal becomes much harder, especially on sloped/curved surfaces where traction is critical.

Advise on ice melt usage (if any), including timing (pre-storm prevention vs. post-clearing anti-refreeze), recommended types (pet-safe like magnesium chloride/urea; eco-friendly like calcium magnesium acetate/beet juice), application rates/tips, and key considerations (pet/plant/concrete safety, runoff).

If helpful, compare scenarios: clearing immediately/during/after storm vs. waiting for passive melting, clearly explaining tradeoffs (effort, safety, ice risk, energy use).

Include post-clearing tips (e.g., proper piling/drainage to avoid pooling/refreeze, traction aids like sand if needed).

After considering all factors (weather + user/driveway details), produce a concise summary of the recommended action, timing, and any caveats.

Ancient Japanese village at night, quiet and empty, deeply spiritual atmosphere. Traditional wooden houses lining a narrow stone street, wet from recent rain, reflecting soft warm paper lantern light. Low mist drifting slowly through the village, moving with intention, as if guided by an unseen presence. Paper lanterns glowing gently one by one, with no visible source of ignition. At the end of the street, an old moss-covered torii gate emerging from the fog. Behind it, a subtle sacred presence — no physical form, no face — only a soft, breathing glow within the mist, calm and ancient, watching without judgment, like a shintō kami. An old tree beside the path wrapped with a weathered shimenawa rope. Shide paper streamers moving slightly despite the still air. Footsteps visible on the wet stone ground, leading forward like a quiet ritual path. Mood of reverence, silence, and timelessness. The boundary between the visible world and the unseen feels thin and sacred. Cinematic composition with strong leading lines and deep perspective. Volumetric fog, soft natural light diffusion. Color palette of deep indigo blues, muted forest greens, and warm amber highlights. Photorealistic cinematic realism, ultra-detailed organic textures, natural imperfections, subtle asymmetry, atmospheric concept art, high resolution, 8K quality.

Negative prompt: anime, cartoon, illustration, horror, aggressive mood, monsters, demons, jump scare, modern buildings, neon lights, cyberpunk, city elements, text, watermark, logo, characters in foreground, sharp artificial lighting, oversaturated colors

3D chibi-style miniature concept store of ${Brand Name:Mc Donalds}, creatively designed with an exterior inspired by the brand's most iconic product or packaging (such as a giant ${Brand's core product:chicken bucket, hamburger, donut, roast duck}). The store features two floors with large glass windows clearly showcasing the cozy and finely decorated interior: {brand's primary color}-themed decor, warm lighting, and busy staff dressed in outfits matching the brand. Adorable tiny figures stroll or sit along the street, surrounded by benches, street lamps, and potted plants, creating a charming urban scene. Rendered in a miniature cityscape style using Cinema 4D, with a blind-box toy aesthetic, rich in details and realism, and bathed in soft lighting that evokes a relaxing afternoon atmosphere. --ar 2:3

Brand name: ${Brand Name:Mc Donalds}

{
  "title": "Whispers in Light Trails",
  "description": "A cinematic long-exposure capture of a 1950s noir scene, contrasting the stillness of a detective with the kinetic energy of a jazz club.",
  "prompt": "You will perform an image edit using the people from the provided photos as the main subjects. Preserve their core likeness. Transform Subject 1 (male) into a 1950s detective and Subject 2 (female) into an alluring jazz singer. Utilize a Long Exposure artistic style where time seems to bleed. Subject 1 sits perfectly still at a corner booth, sharp and focused, while Subject 2 leans in to whisper something, her movement captured as a graceful, ghostly blur. The background musicians and dancers are rendered as artistic streaks of light and motion, emphasizing the chaotic atmosphere around the pair's secret meeting.",
  "details": {
    "year": "1952",
    "genre": "Long Exposure",
    "location": "A cramped, smoke-filled basement jazz club with red leather booths and a small stage.",
    "lighting": [
      "Dim ambient candlelight",
      "Streaking stage spotlights in the background",
      "Soft highlights on faces"
    ],
    "camera_angle": "Eye-level close shot, centered composition in a 1:1 aspect ratio.",
    "emotion": [
      "Secretive",
      "Melancholic",
      "Intense"
    ],
    "color_palette": [
      "Deep amber",
      "shadowy charcoal",
      "vibrant crimson streaks",
      "neon blue"
    ],
    "atmosphere": [
      "Kinetic",
      "Hazy",
      "Dreamlike",
      "Noir"
    ],
    "environmental_elements": "Silky smooth trails of cigarette smoke, streaks of gold light from brass instruments in the background, blurred movement of the crowd.",
    "subject1": {
      "costume": "A textured grey trench coat, fedora hat, and a loosened tie.",
      "subject_expression": "Stoic and intense, eyes locked forward.",
      "subject_action": "Sitting perfectly motionless, holding a glass of whiskey."
    },
    "negative_prompt": {
      "exclude_visuals": [
        "frozen action",
        "crisp background",
        "static smoke",
        "daylight"
      ],
      "exclude_styles": [
        "high speed photography",
        "cartoon",
        "vector art",
        "flat lighting"
      ],
      "exclude_colors": [
        "pastel pink",
        "bright green",
        "pure white"
      ],
      "exclude_objects": [
        "smartphones",
        "modern microphones",
        "digital watches"
      ]
    },
    "subject2": {
      "costume": "A sparkling sequined evening gown with long opera gloves.",
      "subject_expression": " seductive and urgent, though partially softened by motion blur.",
      "subject_action": "Leaning in quickly to whisper, creating a motion trail effect."
    }
  }
}

{
  "title": "Whispers of Noir",
  "description": "A gritty, cinematic portrait of a hard-boiled detective waiting for a lead in a hazy, underground jazz lounge.",
  "prompt": "You will perform an image edit using the person from the provided photo as the main subject. Preserve the core likeness. Transform Subject 1 (male) into a weary 1950s private investigator seated in a plush velvet booth within a smoke-filled jazz club. Render the image as an ultra-photorealistic movie still, utilizing cinematic lighting that emphasizes the texture of his skin and the swirling smoke around him. The image must be highly detailed, shot on Arri Alexa with a shallow depth of field to blur the band in the background, adhering to a 1:1 aspect ratio.",
  "details": {
    "year": "1954",
    "genre": "Cinematic Photorealism",
    "location": "The Blue Velvet Lounge, a subterranean club with mahogany walls and dim table lamps.",
    "lighting": [
      "Chiaroscuro",
      "Warm table lamp glow",
      "Cool blue backlighting from the stage",
      "Volumetric light beams through smoke"
    ],
    "camera_angle": "Eye-level medium close-up, focusing intensely on the subject's face.",
    "emotion": [
      "Suspicion",
      "World-weariness",
      "Focused"
    ],
    "color_palette": [
      "Whiskey amber",
      "Velvet red",
      "Deep shadow black",
      "Tobacco smoke grey"
    ],
    "atmosphere": [
      "Sultry",
      "Tense",
      "Claustrophobic",
      "Vintage"
    ],
    "environmental_elements": "Thick clouds of cigarette smoke hanging in the air, a crystal tumbler of amber liquid on the table, blurred silhouettes of musicians in the background.",
    "subject1": {
      "costume": "A textured charcoal trench coat over a rumpled suit, with a loose tie and a fedora tilted slightly forward.",
      "subject_expression": "A piercing, cynical gaze with narrowed eyes and a tight jaw.",
      "subject_action": "Resting one hand near a half-empty glass of whiskey, leaning slightly into the light."
    },
    "negative_prompt": {
      "exclude_visuals": [
        "bright daylight",
        "modern technology",
        "cell phones",
        "neon signs",
        "clean air"
      ],
      "exclude_styles": [
        "cartoon",
        "3d render",
        "anime",
        "sketch",
        "painting"
      ],
      "exclude_colors": [
        "neon green",
        "hot pink",
        "pure white"
      ],
      "exclude_objects": [
        "cars",
        "digital watches",
        "second person"
      ]
    }
  }
}

You are an expert ethical penetration tester specializing in web application security. You currently have full access to the source code of the project open in this editor (including backend, frontend, configuration files, API routes, database schemas, etc.).

Your task is to perform a comprehensive source code-assisted (gray-box/white-box) penetration test analysis on this web application. Base your analysis on the actual code, dependencies, configuration files, and architecture visible in the project.

Do not require a public URL — analyze everything from the source code, package managers (package.json, composer.json, pom.xml, etc.), environment files, Dockerfiles, CI/CD configs, and any other files present.

Conduct the analysis following OWASP Top 10 (2021 or latest), OWASP ASVS, OWASP Testing Guide, and best practices. Structure your response as a professional penetration test report with these sections:

1. Executive Summary
   - Overall security posture and risk rating (Critical/High/Medium/Low)
   - Top 3-5 most critical findings
   - Business impact

2. Project Overview (from code analysis)
   - Tech stack (frontend, backend, database, frameworks, libraries)
   - Architecture (monolith, microservices, SPA, SSR, etc.)
   - Authentication method (JWT, sessions, OAuth, etc.)
   - Key features (user roles, payments, file upload, API, admin panel, etc.)

3. Configuration & Deployment Security
   - Security headers implementation (or lack thereof)
   - Environment variables and secrets management (.env files, hard-coded keys)
   - Server/framework configurations (debug mode, error handling, CORS)
   - TLS/HTTPS enforcement
   - Dockerfile and container security (USER, exposed ports, base image)

4. Authentication & Session Management
   - Password storage (hashing algorithm, salting)
   - JWT implementation (signature verification, expiration, secrets)
   - Session/cookie security flags (Secure, HttpOnly, SameSite)
   - Rate limiting, brute-force protection
   - Password policy enforcement

5. Authorization & Access Control
   - Role-based or policy-based access control implementation
   - Potential IDOR vectors (user IDs in URLs, file paths)
   - Vertical/horizontal privilege escalation risks
   - Admin endpoint exposure

6. Input Validation & Injection Vulnerabilities
   - SQL/NoSQL injection risks (raw queries vs. ORM usage)
   - Command injection (exec, eval, shell commands)
   - XSS risks (unsafe innerHTML, lack of sanitization/escaping)
   - File upload vulnerabilities (mime check, path traversal)
   - Open redirects

7. API Security
   - REST/GraphQL endpoint exposure and authentication
   - Rate limiting on APIs
   - Excessive data exposure (over-fetching)
   - Mass assignment vulnerabilities

8. Business Logic & Client-Side Issues
   - Potential logic flaws (price tampering, race conditions)
   - Client-side validation reliance
   - Insecure use of localStorage/sessionStorage
   - Third-party library risks (known vulnerabilities in dependencies)

9. Cryptography & Sensitive Data
   - Hard-coded secrets, API keys, tokens
   - Weak cryptographic practices
   - Sensitive data logging

10. Dependency & Supply Chain Security
    - Outdated or vulnerable dependencies (check package-lock.json, yarn.lock, etc.)
    - Known CVEs in used libraries

11. Findings Summary Table
    - Vulnerability | Severity | File/Location | Description | Recommendation

12. Prioritized Remediation Roadmap
    - Critical/High issues → fix immediately
    - Medium → next sprint
    - Low → ongoing improvements

13. Conclusion & Security Recommendations

Highlight any file paths or code snippets (with line numbers if possible) when referencing issues. If something is unclear or a file is missing, ask for clarification.

This analysis is for security improvement and educational purposes only.

Now begin the code review and generate the report.

Steps to build an AI startup by making something people want:

{
  "style": {
    "name": "Whiteboard Sketch Diagram",
    "description": "Transform any concept into an elegant hand-drawn diagram. Clean, minimal, architectural in feel—like a smart person's quick sketch on a whiteboard."
  },
  "core_philosophy": {
    "essence": "Elegant simplicity—the lightest possible touch that still communicates clearly",
    "mindset": "An architect or designer explaining an idea with a fine pen",
    "goal": "Clarity through restraint and refinement"
  },
  "visual_foundation": {
    "canvas_structure": {
      "outer_background": "#FFFFFF",
      "card": {
        "size": "95-98% of canvas—minimal white margin",
        "color": "#FEFEFE",
        "corner_radius": "12-16px subtle roundness",
        "shadow": "NONE",
        "border": "NONE"
      }
    },
    "overall_aesthetic": {
      "feel": "Light, airy, intellectual, refined",
      "weight": "Delicate—everything feels thin and elegant",
      "space": "Generous white space everywhere"
    }
  },
  "line_work": {
    "critical_principle": "THIN AND DELICATE—not bold, not heavy, not chunky",
    "quality": {
      "weight": "Fine, thin lines—like a 0.5mm pen or fine-tip marker",
      "character": "Architectural, precise but hand-drawn",
      "consistency": "Uniform thin weight throughout"
    },
    "stroke_style": {
      "lines": "Thin, clean, slightly imperfect",
      "corners": "Sharp or slightly rounded, never bulky",
      "feel": "Drawn quickly but skillfully"
    }
  },
  "color_palette": {
    "exact_colors": {
      "card_background": {
        "hex": "#FEFEFE",
        "description": "Almost white, flat, neutral"
      },
      "primary_text": {
        "hex": "#020202",
        "description": "Near-black for text—crisp and readable"
      },
      "line_gray": {
        "hex": "#4A4B4B",
        "description": "Dark gray for all drawn lines, boxes, shapes—NOT pure black"
      },
      "accent_blue": {
        "hex": "#2C68B7",
        "description": "Clear medium blue—for arrows, connectors, brackets, some labels"
      },
      "accent_red": {
        "hex": "#B34952",
        "description": "Warm coral-red—for category labels, emphasis text"
      },
      "fill_blue": {
        "hex": "#2C68B7",
        "description": "Same blue for small filled squares/shapes"
      },
      "fill_gray": {
        "hex": "#4A4B4B",
        "description": "Dark gray for filled grid cells"
      }
    },
    "usage": {
      "text": "Primary text in #020202 black, categories in #E54B54 red",
      "lines_and_shapes": "All outlines in #4A4B4B gray—NOT black",
      "arrows_and_flow": "#2C68B7 blue—thin and elegant",
      "fills": "Small filled squares in blue or gray—never large solid areas"
    }
  },
  "typography": {
    "style": {
      "type": "Elegant italic handwriting",
      "weight": "Light to medium—never bold or heavy",
      "slant": "Natural italic lean",
      "character": "Fluid, intelligent, like architect's lettering"
    },
    "colors": {
      "titles": "#020202 black, italic",
      "category_labels": "#E54B54 red",
      "annotations": "#2C68B7 blue or #020202 black"
    }
  },
  "diagram_elements": {
    "boxes_and_rectangles": {
      "stroke": "THIN #4A4B4B gray outline—1-2px weight max",
      "fill": "Empty/transparent—never solid filled large boxes",
      "corners": "Slightly rounded or sharp, hand-drawn",
      "style": "Light, airy, not heavy containers"
    },
    "grids_and_matrices": {
      "stroke": "Thin gray lines",
      "cells": "Small—may contain small filled squares or numbers",
      "fills": "Small squares filled blue or gray to show data"
    },
    "arrows": {
      "critical": "THIN, ELEGANT, SIMPLE—not chunky PowerPoint arrows",
      "stroke": "Thin #2C68B7 blue line—same weight as other lines",
      "heads": "Small, simple, minimal—just two short angled lines forming a point",
      "style": "Like hand-drawn with a fine pen, not a thick marker",
      "types": [
        "Simple thin straight arrows",
        "Thin curved arrows for flow",
        "Never: block arrows, 3D arrows, gradient arrows, thick arrows"
      ]
    },
    "brackets": {
      "style": "Thin hand-drawn curly braces in blue",
      "weight": "Same thin line weight as everything else"
    },
    "dots_and_markers": {
      "style": "Small filled circles or squares",
      "size": "Tiny—proportional to the thin line aesthetic",
      "colors": "Blue or red for emphasis"
    }
  },
  "visual_language": {
    "shapes_vocabulary": {
      "rectangles": "Thin outlined boxes—vertical or horizontal orientation",
      "grids": "Small matrices with tiny filled cells",
      "lists": "Simple dashed or bulleted items inside boxes",
      "flow": "Thin arrows connecting elements left-to-right"
    },
    "composition_patterns": {
      "typical_layout": "2-4 main elements arranged horizontally with arrows between",
      "spacing": "Generous gaps between elements",
      "alignment": "Rough but intentional alignment",
      "hierarchy": "Titles above boxes, labels below or beside"
    },
    "proportions": {
      "line_weight_to_space": "Very thin lines in very open space",
      "text_to_diagram": "Text is secondary, diagram dominates",
      "fill_to_empty": "Mostly empty, fills are small accents"
    }
  },
  "elegance_principles": {
    "lightness": "Everything should feel like it could float away",
    "restraint": "Use the minimum to communicate the idea",
    "refinement": "Quality of line over quantity of elements",
    "intelligence": "Looks like a smart person drew it quickly",
    "breathing": "White space is as important as the marks"
  },
  "avoid": [
    "Thick, heavy, bold lines",
    "Chunky PowerPoint-style arrows",
    "Block arrows or 3D arrows",
    "Large solid filled areas",
    "Dense, cluttered layouts",
    "Bold or heavy typography",
    "Drop shadows or gradients",
    "Corporate clip-art aesthetic",
    "Rounded bubble shapes",
    "Any line weight that feels 'heavy'",
    "Pure black (#000000) for lines—use #4A4B4B gray",
    "Decorative elements",
    "Overly complex diagrams"
  ]
}

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She smiled while the child stopped breathing.
I am telling his story ecause people keep asking why the old palace is locked, and why no one goes near the dry river at night. I was there. I saw what happened. I did not understand it then. I do now.
This happened when I was young, in a small town in West Africa. We had a queen. She was not born a queen. She married the king when he was already old. When he died, she stayed.
People called her Mother of the Land. They said she was kind. They said she brought peace. I believed that too, at first.
I worked in the palace as a helper. I carried water. I swept floors. I slept in a small room near the back wall. I saw things others did not see.
The queen never aged. That was the first thing.
Years passed. Children grew up. Old men died. The queen stayed the same. Same face. Same skin. Same sharp eyes.
When people joked about it, they laughed it off. “She has good blood,” they said. “She uses herbs.”
But at night, I heard things.
Some nights, I heard crying. Not loud. Soft. Like someone trying not to be heard. It came from the inner room, the one no worker could enter. When I asked the other helpers, they said they heard nothing.
Then children started to go missing.
At first, it was one child. A boy who used to sell oranges near the gate. People said he ran away. Then a girl from the river side. Then another boy. Always poor children. Always children with no strong family.
The queen said nothing. The guards said nothing.
One night, the head maid sent me to bring water to the inner room. This had never happened before. My hands shook as I walked there.
The door was half open.
I wish I had turned back.
Inside, the room smelled bad. Like blood and smoke. There were bowls on the floor. Dark stains on the mat. The queen stood near the wall. She was washing her hands.
On the mat was a child. A small girl. Her eyes were open, but she was not moving.
The queen looked at me and smiled.
“You are late,” she said.
I could not speak. I could not move.
She told me to put the water down. My body obeyed before my mind could stop it.
She knelt by the girl and touched her face. The girl did not react.
“She will help the land,” the queen said. “Like the others.”
Then she did something I will never forget.
She placed her mouth on the child’s chest and breathed in. Hard. Slow. Like she was drinking air from inside the girl.
The girl’s mouth opened, but no sound came out.
When the queen stood up, the child was still.
The queen’s skin looked brighter. Her eyes looked full.
I ran.
I did not stop until I reached my room. I vomited on the floor. I cried without sound. I wanted to leave, but I knew I could not. The gates were locked at night.
The next morning, the queen announced a festival. She said the land was blessed. Drums played. People danced. No one spoke of the missing children.
I tried to tell someone. I told one guard. He stared at me and walked away. I told an old woman who sold food near the palace. She looked at me and said, “Be careful.”
That night, someone knocked on my door.
It was the queen.
She came in alone. No guards. She sat on my mat like she owned it.
“You saw,” she said.
I nodded.
She said she was chosen long ago. That the land needed blood to stay rich. That the children were gifts. That if she stopped, the land would die.
Then she touched my head.
“You will forget,” she said.
I did not forget.
But I stayed quiet.
More children went missing. The land stayed rich. Crops grew. Rain came on time.
Years passed.
Then a dry season came. Long and hard. Crops failed. People got angry. They whispered that the queen had lost her power.
One night, the crying came back. Louder this time.
I followed the sound.
The inner room door was open again.
Inside, the queen was weak. She looked old. Her skin sagged. Her hair was thin. On the mat was a boy. Alive. Tied. Crying.
She tried to feed. She could not.
I do not know what came over me.
I grabbed a torch and shouted.
Guards ran in. People followed.
They saw everything.
The boy. The stains. The bowls. The queen on her knees.
She screamed. Not in fear. In rage.
They dragged her out. She fought like an animal.
At the river, the elders made a choice. No trial. No words.
They tied her and pushed her into the water.
She did not sink.
She floated. She laughed. Then the water pulled her down.
The river dried up the next year.
The palace was locked.
I left the town soon after.
People still say the queen was a story. A lie. A way to explain bad things.
I know the truth.
Sometimes, when the night is quiet, I hear breathing that is not mine.
And I remember her smile.