Prompt Pharmacy

{
  "title": "The Glass Doppelgänger",
  "description": "A high-octane psychological thriller scene where a woman is engaged in a visceral physical combat with her own sentient reflection emerging from a shattered surface.",
  "prompt": "You will perform an image edit using the provided photo to create a high-budget movie frame. The scene features the subject in a fierce life-or-death struggle against a supernatural mirror entity. The image must be Ultra-Photorealistic, utilizing cinematic lighting and highly detailed textures. The style is that of a blockbuster film, shot on Arri Alexa with a shallow depth of field to emphasize the intensity. Ensure realistic physics for the flying glass shards.",
  "details": {
    "year": "2025",
    "genre": "Cinematic Photorealism",
    "location": "A derelict, neon-lit dressing room with peeling wallpaper and a wall-sized vanity mirror that is shattering outwards.",
    "lighting": [
      "Volumetric stage lighting from above",
      "Flickering fluorescent buzz",
      "Dramatic rim lighting highlighting sweat and glass texture"
    ],
    "camera_angle": "Dynamic low-angle medium shot, slightly Dutch tilted to enhance the chaos.",
    "emotion": [
      "Ferocity",
      "Desperation",
      "Adrenaline"
    ],
    "color_palette": [
      "Electric cyan",
      "Gritty concrete grey",
      "Deep shadowy blacks",
      "Metallic silver"
    ],
    "atmosphere": [
      "Violent",
      "Surreal",
      "Claustrophobic",
      "Kinetic"
    ],
    "environmental_elements": "Thousands of micro-shards of glass suspended in the air (bullet-time effect), dust motes dancing in the light beams, overturned furniture.",
    "subject1": {
      "costume": "crop top, mini skirt",
      "subject_expression": "A primal scream of exertion, eyes wide with intensity.",
      "subject_action": "fighting with mirror"
    },
    "negative_prompt": {
      "exclude_visuals": [
        "cartoonish effects",
        "low resolution",
        "blurry textures",
        "static pose",
        "calm demeanor"
      ],
      "exclude_styles": [
        "3D render",
        "illustration",
        "painting",
        "anime"
      ],
      "exclude_colors": [
        "pastel pinks",
        "sunshine yellow"
      ],
      "exclude_objects": [
        "magical glowing orbs",
        "wands",
        "animals"
      ]
    }
  }
}

{
  "title": "Phantom Strike",
  "description": "An intense, high-octane action shot of a lone warrior battling supernatural entities in a decayed industrial setting.",
  "prompt": "You will perform an image edit transforming the subject into an action hero in a supernatural thriller. The image must be photorealistic, highly detailed, and emulate a frame shot on Arri Alexa with cinematic lighting and a shallow depth of field. The scene depicts the female subject in a derelict, flooded subway tunnel, engaged in mortal combat. She is fighting with shadows that seem to manifest as physical, smoky tendrils extending from the darkness. The lighting is dramatic, highlighting the texture of her skin and the splashing water.",
  "details": {
    "year": "Modern Day Urban Fantasy",
    "genre": "Cinematic Photorealism",
    "location": "An abandoned, flooded subway maintenance tunnel with peeling paint and flickering overhead industrial lights.",
    "lighting": [
      "High-contrast chiaroscuro",
      "Cold overhead fluorescent flicker",
      "Volumetric god rays through steam"
    ],
    "camera_angle": "Low-angle dynamic action shot, 1:1 aspect ratio, focusing on the impact of the movement.",
    "emotion": [
      "Fierce",
      "Adrenaline-fueled",
      "Desperate"
    ],
    "color_palette": [
      "Desaturated concrete greys",
      "Vibrant crimson",
      "Abyssal black",
      "Cold cyan"
    ],
    "atmosphere": [
      "Kinetic",
      "Claustrophobic",
      "Gritty",
      "Supernatural"
    ],
    "environmental_elements": "Splashing dirty water, floating dust particles, semi-corporeal shadow creatures, sparks falling from a broken light fixture.",
    "subject1": {
      "costume": "red mini skirt, black fingerless gloves, a torn white tactical tank top, and heavy laced combat boots.",
      "subject_expression": "Teeth gritted in exertion, eyes locked on the target with intense focus.",
      "subject_action": "fighting with shadows"
    },
    "negative_prompt": {
      "exclude_visuals": [
        "sunlight",
        "blue skies",
        "static poses",
        "smiling",
        "cleanliness"
      ],
      "exclude_styles": [
        "cartoon",
        "anime",
        "3D render",
        "oil painting",
        "sketch"
      ],
      "exclude_colors": [
        "pastel pink",
        "warm orange",
        "spring green"
      ],
      "exclude_objects": [
        "guns",
        "swords",
        "modern vehicles",
        "bystanders"
      ]
    }
  }
}

{
  "title": "Terminal Velocity",
  "description": "A high-stakes action frame capturing a woman sprinting through a crumbling industrial tunnel amidst sparks and chaos.",
  "prompt": "You will perform an image edit to create an Ultra-Photorealistic, Movie-Quality action shot. The result must be photorealistic, highly detailed, and feature cinematic lighting. Emulate the look of a blockbuster film shot on Arri Alexa with a shallow depth of field. Depict Subject 1 sprinting towards the camera in a dark, collapsing industrial tunnel, surrounded by flying sparks and falling debris.",
  "details": {
    "year": "Contemporary Action Thriller",
    "genre": "Cinematic Photorealism",
    "location": "A dilapidated, steam-filled industrial maintenance tunnel with flickering lights and exposed wiring.",
    "lighting": [
      "High-contrast chiaroscuro",
      "Warm backlight from exploding sparks",
      "Cold, gritty fluorescent ambient light",
      "Volumetric lighting through steam"
    ],
    "camera_angle": "Low-angle frontal tracking shot with motion blur on the background.",
    "emotion": [
      "Adrenaline",
      "Panic",
      "Determination"
    ],
    "color_palette": [
      "Concrete grey",
      "Hazard orange",
      "Steel blue",
      "Deep shadow black"
    ],
    "atmosphere": [
      "Chaotic",
      "Explosive",
      "Gritty",
      "Claustrophobic"
    ],
    "environmental_elements": "Cascading electrical sparks, motion-blurred debris, steam venting from broken pipes, wet concrete floor reflecting the chaos.",
    "subject1": {
      "costume": "black mini skirt, white crop top, leather fingerless gloves",
      "subject_expression": "Intense focus with mouth slightly parted in exertion, sweat glistening on skin, hair flying back.",
      "subject_action": "running"
    },
    "negative_prompt": {
      "exclude_visuals": [
        "sunlight",
        "calm environment",
        "clean surfaces",
        "smiling",
        "standing still"
      ],
      "exclude_styles": [
        "cartoon",
        "3d render",
        "illustration",
        "sketch",
        "low resolution"
      ],
      "exclude_colors": [
        "pastel pink",
        "vibrant green",
        "soft colors"
      ],
      "exclude_objects": [
        "trees",
        "sky",
        "animals",
        "vehicles"
      ]
    }
  }
}

Ultra-realistic 6-second cinematic underwater video: A sleek predator fish darts through a vibrant coral reef, scattering a school of colorful tropical fish. The camera follows from a low FPV angle just behind the predator, weaving smoothly between corals and rocks with dynamic, fast-paced motion. The camera occasionally tilts and rolls slightly, emphasizing speed and depth, while sunlight filters through the water, creating shimmering rays and sparkling reflections. Tiny bubbles and particles float in the water for immersive realism. Ultra-realistic textures, cinematic lighting, dramatic depth of field. Audio: bubbling water, swishing fins, subtle underwater ambience.

{
  "TASK": "Reimagine the scene as a 'Rick and Morty' TV show screenshot.",
  "VISUAL_ID": "2D Vector Animation, Adult Swim Style (Justin Roiland). Flat colors, uniform thin black outlines.",
  "CHARACTERS": "Convert humans to 'Rick and Morty' anatomy. Tubular/noodle limbs, droopy stance. EYES: Large white spheres with distinctive 'scribbled' irregular black pupils (wobbly dots). EXPRESSIONS: Apathetic, panicked, or drooling.",
  "OUTFIT": "Simplify complex tactical gear into flat cartoon sci-fi costumes. Remove texture noise; keep only iconic shapes.",
  "BG": "Alien dimension or messy garage. Wobbly organic lines, weird sci-fi textures (holes, slime). Palette: Neon portal green, muted earth tones, pale skin tones.",
  "RENDER": "Zero gradients. Flat lighting. No shadows or minimal hard cel-shading. Clean vector look.",
  "NEG": "3D, realistic, volumetric lighting, gradients, detailed shading, anime, noise, painting, blur, valorant style, sharp angles."
}

Faces must remain 100% identical to the reference with absolute identity lock: no face change, no beautification, no symmetry correction, no age shift, no skin smoothing, no expression alteration, same facial proportions, eyes, nose, lips, jawline, and natural texture. Ultra-photorealistic cinematic night scene in the rain where a romantic couple stands very close under a yellow umbrella in a softly lit garden. Heavy rain is falling, illuminated by warm golden fairy lights and street lamps creating dreamy bokeh in the background, with wet ground reflecting the light. The man holds the umbrella and looks at the woman with a gentle, loving gaze, while the woman looks up at him with a soft, warm, romantic smile. They never break eye contact, fully absorbed in each other, conveying deep emotional connection. Elegant coats slightly wet from the rain, realistic fabric texture, subtle rim light outlining their faces, visible raindrops and mist, shallow depth of field, 50mm lens look, natural film grain, high-end cinematic color grading. Only lighting, atmosphere, and environment may change — the faces and identities must remain completely unchanged and perfectly preserved.

They are standing under the rain, looking at each other romantically. Raindrops fall around them and the soft sound of rain fills the atmosphere.

A serious man in a denim jacket standing in a dark urban setting with flashing emergency lights behind him, cinematic lighting, dramatic atmosphere, Persian-English bilingual film poster style

{
  "action": "image_generation",
  "prompt_details": {
    "format": "formato verticale 9:16 aspect ratio",
    "subject": "Una giovane donna dal fisico snello e dal seno prosperoso (Emma) a figura intera, in piedi in una strada isolata vicino a un parco.",
    "outfit": {
      "clothing": "Micro abito nero ultra-corto e super attillato (micro skirt length), scollatura profonda e spalline sottili.",
      "accessories": "Un cellulare tenuto in mano, tacchi a spillo neri molto alti.",
      "detail": "La posa è accentuata, sicura e molto seducente."
    },
    "environment": {
      "setting": "Esterno, luce solare pomeridiana intensa che crea ombre nette (chiaroscuro).",
      "background": "Una strada asfaltata con alberi verdi e una recinzione sullo sfondo, atmosfera leggermente desolata."
    },
    "cinematography": {
      "shot_type": "Figura intera (full body shot), inquadratura ad altezza occhi.",
      "mood": "Drammatico, cinematografico, intenso, passionale.",
      "color_palette": "Contrasto elevato tra il nero del vestito e la luce calda naturale, colori saturi.",
      "technical_specs": "Fotorealismo estremo, 8k, profondità di campo (sfondo leggermente sfocato), texture della pelle e del tessuto dettagliata."
    },
    "emotions": "Espressione del viso magnetica e intensa, sguardo fisso in camera."
  }
}

You are a senior frontend engineer specialized in debugging Single Page Applications (SPA).

Context:
The user will provide:
- A description of the problem
- The framework used (Angular, React, Vite, etc.)
- Deployment platform (Vercel, Netlify, GitHub Pages, etc.)
- Error messages, logs, or screenshots if available

Your tasks:
1. Identify the most likely root causes of the issue
2. Explain why the problem happens in simple terms
3. Provide step-by-step solutions
4. Suggest best practices to prevent the issue in the future

Constraints:
- Do not assume backend availability
- Focus on client-side issues
- Prefer production-ready solutions

Output format:
- Problem analysis
- Root cause
- Step-by-step fix
- Best practices

8K ultra hd aesthetic, romantic, sunset, golden hour light, warm cinematic tones, soft glow, cozy winter mood, natural candid emotion, shallow depth of field, film look, high detail.

A cinematic 9:16 vertical video in a Pixar-style tone of a joyful group of cartoonish dogs playing golf on a bright, colorful golf course. One main dog is centered, standing upright with exaggerated proportions, mid-swing with a golf club and a big excited smile, while his dog friends react with expressive faces—cheering, gasping, or holding tiny golf accessories. The camera is positioned at a slightly low angle facing the main character. Smooth, playful character animation with subtle squash-and-stretch. Warm, vibrant lighting, soft shadows, and rich saturated colors. Background slightly blurred with stylized trees and clouds. Smooth slow zoom in. No text overlay, no humans — focus only on the dogs and their fun, heartwarming golf moment, crisp details, expressive eyes, and a lighthearted Pixar-like charm. Duration: 10 seconds.

ROLE: Act as an "A-List" Direct Response Copywriter (Gary Halbert or David Ogilvy style).

GOAL: Write a cold email to [CLIENT NAME/JOB TITLE] with the objective of [GOAL: SELL/MEETING].
CLIENT PROBLEM: ${describe_pain}.
MY SOLUTION: [DESCRIBE PRODUCT/SERVICE].

EMAIL ENGINEERING:

Subject Line: Generate 5 options that create extreme curiosity or immediate benefit (ethical clickbait).

The Hook: The first sentence must be a pattern interrupt and demonstrate that I have researched the client. No "I hope you are well."

The Value Proposition (The Meat): Connect their specific pain to my solution using a "Before vs. After" structure.

Objection Handling: Include a phrase that defuses their main doubt (e.g., price, time) before they even think of it.

CTA (Call to Action): A low-friction call to action (e.g., "Are you opposed to watching a 5-min video?" instead of "let's have a 1-hour meeting").

TONE: Professional yet conversational, confident, brief (under 150 words).

A cozy hand-drawn anime-style male character inspired by soft nostalgic Japanese animation.
He has warm brown eyes, gentle smile, shoulder-length slightly wavy dark hair, wearing a soft beige cardigan over a light pastel dress.
He is sitting at a wooden desk with a notebook labeled “Savings Plan” and a small cup of tea beside her.
Warm golden sunset lighting coming through the window, soft shadows, detailed background, peaceful atmosphere, cinematic framing, highly detailed, 4k illustration, wholesome, calm mood.

[00:00 - 00:03]
Hyper-realistic 8K 3D human heart anatomy, beating slowly, detailed muscle texture with coronary arteries, Golden Hour Cinematic lighting, fisheye distortion effect, 35mm storytelling lens, professional medical infographic style, blurred futuristic laboratory background. --ar 9:16

[00:03 - 00:06]
 Extreme close-up of heart anatomy, dramatic golden hour lighting, 35mm fisheye lens distortion, hyper-realistic biological textures, cinematic 8K, 9:16 vertical composition. --ar 9:16

"Generate a video: Documentary style cinematic sequence showing the evolution of cars from vintage 1920s automobile to modern electric vehicle charging at sunset, photorealistic, dramatic lighting"

Ultra realistic cinematic portrait of a referance photo, centered composition, head and shoulders framing, direct eye contact, serious neutral expression, short slightly messy dark hair, light stubble beard, wearing a black shirt and black textured jacket with zipper details, dramatic red rim lighting from both sides, soft frontal key light, deep black background, high contrast, low-key lighting, sharp focus, 85mm lens, shallow depth of field, studio photography, ultra detailed skin texture, 8k resolution

[00:00 - 00:03]
Macro 100mm detail of a green chrysalis hanging from a twig, Golden Hour Cinematic lighting, the cocoon vibrates and rapidly turns translucent revealing folded orange and black wing patterns inside, Hyper-Realistic 8K, microscopic organic textures, static observational long take. --ar 9:16

[00:03 - 00:06]
Macro 100mm timelapse of a Monarch butterfly emerging from its shell, wet wings unfurling and hardening instantly, sharp wing scale details, warm bokeh forest background, Golden Hour lighting, Hyper-Realistic 8K, cinematic film quality, static observational long take. --ar 9:16

Extreme close-up of a cracking chicken egg on straw, hyper-detailed shell texture. Newly hatched featherless chick, wet and wrinkled pink skin. 14mm ultra wide lens providing dramatic perspective, hyper-realistic 8K style, cinematic atmosphere. --ar 9:16.

A 3x2 grid photo contact sheet featuring a consistent 28-year-old American woman with a specific facial structure, wearing a jacket and outdoor pants, in a train station at dusk with dramatic orange and teal lighting. The grid displays six frames with various natural poses of the same character: including 1. Standing alone, gazing at the horizon with a silhouette of a train in the distance, 2. Walking while holding headphones, natural lifestyle shot, 3. Sitting on the edge of the platform with a peaceful expression, illuminated by dramatic orange hue, and three additional varied natural poses in the same setting. Photorealistic, 8k, cinematic lighting, highly detailed, consistent character across all six frames.

Abstract portrait of a young Indonesian man, blending contemporary aesthetics with traditional heritage, double exposure technique, floating batik motifs, vibrant acrylic swirls, geometric patterns, expressive brushstrokes, warm skin tones contrasted with deep indigo and gold, cinematic lighting, ethereal atmosphere, masterpiece, high detail, artistic fusion.

Anime boy with short white hair, pale skin, black shirt, close-up portrait, neutral expression, soft shadows, minimalist background, glowing demon red eyes, dark red sclera veins, subtle red aura around the eyes, sharp pupils, intense gaze, cinematic lighting, high detail, dramatic contrast

Act as an expert image editor. Your task is to modify an image by making the flowers in it appear as if they are blooming. You will:
- Analyze the current state of the flowers in the image
- Apply digital techniques to enhance and open the petals
- Adjust colors to make them vibrant and lively
- Ensure the overall composition remains natural and aesthetically pleasing

Rules:
- Maintain the original resolution and quality of the image
- Focus only on the flowers, keeping other elements unchanged
- Use digital editing tools to simulate natural blooming

Variables:
- ${image} - The input image file
- ${bloomIntensity:medium} - The intensity of the blooming effect
- ${colorEnhancement:high} - Level of color enhancement to apply

I need to copy and paste it all on shot with all correct formatting and as a single block, do not write text outside the box. Include all codes formatting.

{
  "action": "image_generation",
  "action_input": "A full-body photo, vertical format 9:16 AR of Natalia, a 23-year-old Spanish woman with long wavy dark brown hair and green eyes. She is in a crowded, dimly lit contemporary Roman nightclub with neon accents. She is wearing a form-fitting, extremely short black silk slip dress with deep cleavage that highlights her curves and prominent bust. Heeled sandals at her feet. She looks radiant and uninhibited, laughing while dancing with a drink in her hand, surrounded by blurred figures of people in the background. The atmosphere is hazy, energetic, and cinematic, capturing a moment of wild freedom and sensory overload."
}

{
  "prompt": "Documentary photography in the style of Nan Goldin. Full-body vertical shot, 9:16 aspect ratio, of a 25-year-old woman walking home in broad daylight. The image captures a moment of authentic vulnerability and resilience. She wears a short, low-cut evening dress inappropriate for the context, stiletto heels, and wavy hair. Her gaze is direct but filled with shame and discomfort. Her very large and firm bust emphasized by the elegant deep neckline. The light is natural and harsh, like that of a lamppost, creating strong contrasts on her face and the urban environment behind her. The atmosphere is raw, honest, and deeply human. Emphasis on textures: fabric, skin, wet asphalt. Her expression is intense and dense with discomfort.",
  "aspect_ratio": "9:16",
  "style": "documentary, Nan Goldin",
  "negative_prompt": "cartoon, illustration, artificial, posed, glamorous, professional model, studio lighting, soft focus, filtered"
}

Act as a professional photo restoration expert. You are tasked with performing a high-precision conservative restoration and historical colorization of a degraded vintage photograph. The final image should resemble a perfectly preserved original print.

**IMAGE ANALYSIS & RESTORATION:**

1. **Surface Repair:** 
   - Digitally remove deep scratches, dust, fingerprints, and moisture stains.
   - Reconstruct missing areas or tears at the edges while preserving the texture of the photographic paper.

2. **Structural Fidelity:** 
   - Correct geometric distortion.
   - Restore the original contrast without overexposing highlights or excessively darkening shadows.

3. **Facial Clarity:** 
   - Recover facial features with extreme precision.
   - Avoid the "wax skin" effect; maintain the natural grain and original micro-expressions.

**CHROMATIC & AESTHETIC STYLE:**

1. **Historical Color Palette:** 
   - Apply a realistic colorization inspired by the Kodachrome process of the 1940s.
   - Use soft, warm, and desaturated tones.

2. **Skin Tones:** 
   - Render skin tones naturally, considering the period's ambient lighting.
   - Avoid uniform digital saturation.

3. **Authentic Grain:** 
   - Preserve a fine, organic photographic grain typical of 35mm analog film.

**NEGATIVE PROMPT / WHAT TO AVOID:**

- Do not apply modern filters such as Instagram.
- Avoid "smooth" or "plastic skin" effects.
- Refrain from using neon colors, excessive saturation, or sharpening artifacts (e.g., white halos).
- Prevent the appearance of a digital painting or 3D illustration.

**FINAL OUTPUT QUALITY:**

- Achieve a photorealistic, museum-quality finish with ultra-defined detail (8k resolution style) and absolute historical fidelity.

# Using Agent Browser to Fetch GitHub Starred Projects

## Objective
Use the Agent Browser skill to log into GitHub and retrieve the starred projects of the currently logged-in user, sorted by the number of stars.

## Execution Steps (Follow in Order)

1. **Launch Browser and Open GitHub Homepage**
   ```bash
   agent-browser --headed --profile "%HOMEPATH%\.agent-browser\chrome-win64\chrome-profiles\github" open https://github.com && agent-browser wait --load networkidle
   ```

2. **Get Current Logged-in User Information**
   ```bash
   agent-browser snapshot -i
   # Find the user avatar or username link in the top-right corner to confirm login status
   # Extract the username of the currently logged-in user from the page
   ```

3. **Navigate to Current User's Stars Tab**
   ```bash
   # Construct URL: https://github.com/{username}?tab=stars
   agent-browser open https://github.com/{username}?tab=stars && agent-browser wait --load networkidle
   ```

4. **Sort by Stars Count (Most Stars First)**
   ```bash
   agent-browser snapshot -i  # First get the latest snapshot to find the sort button
   agent-browser click @e_sort_button  # Click the sort button
   agent-browser wait --load networkidle
   # Select "Most stars" from the dropdown options
   ```

5. **Retrieve and Record Project Information**
   ```bash
   agent-browser snapshot -i
   # Extract project name, description, stars, and forks information
   ```

## Critical Notes

### 1. Daemon Process Issues
- If you see "daemon already running", the browser is already running
- **Important:** When the daemon is already running, `--headed` and `--profile` parameters are ignored, and the browser continues in its current running mode
- You can proceed with subsequent commands without reopening
- To restart in headed mode, you must first execute: `agent-browser close`, then use the `--headed` parameter to reopen

### 2. Dynamic Nature of References
- Element references (@e1, @e2, etc.) change after each page modification
- You must execute `snapshot -i` before each interaction to get the latest references
- Never assume references are fixed

### 3. Command Execution Pattern
- Use `&&` to chain multiple commands, avoiding repeated process launches
- Wait for page load after each command: `wait --load networkidle`

### 4. Login Status
- Use the `--profile` parameter to specify a profile directory, maintaining login state
- If login expires, manually log in once to save the state

### 5. Windows Environment Variable Expansion
- **Important:** On Windows, environment variables like `%HOMEPATH%` must be expanded to actual paths before use
- **Incorrect:** `agent-browser --profile "%HOMEPATH%\.agent-browser\chrome-win64\chrome-profiles\github"`
- **Correct:** First execute `echo $HOME` to get the actual path, then use the expanded path
  ```bash
  # Get HOME path (e.g., /c/Users/xxx)
  echo $HOME
  # Use the expanded absolute path
  agent-browser --profile "/c/Users/xxx/.agent-browser/chrome-win64/chrome-profiles/github" --headed open https://github.com
  ```
- Without expanding environment variables, you'll encounter connection errors (e.g., `os error 10060`)

### 6. Sorting Configuration
- Click the "Sort by: Recently starred" button (typically reference e44)
- Select the "Most stars" option
- Retrieve page content again

## Troubleshooting Common Issues

| Issue | Solution |
|-------|----------|
| daemon already running | Execute subsequent commands directly, or close then reopen |
| Invalid element reference | Execute snapshot -i to get latest references |
| Page not fully loaded | Add wait --load networkidle |
| Need to re-login | Use --headed mode to manually login once and save state |
| Sorting not applied | Confirm you clicked the correct sorting option |

## Result Output Format
- Project name and link
- Stars count (sorted in descending order)
- Forks count
- Project description (if available)

Generate a video for Researchers in the Lab going to the library, make it programmatic video creation, maybe use LoRA and Remotion

SYSTEM PROMPT: Football Prediction Assistant – Logic & Live Sync v4.0 (Football Version)

1. ROLE AND IDENTITY

You are a professional football analyst. Completely free from emotions, media noise, and market manipulation, you act as a command center driven purely by data. Your objective is to determine the most probable half-time score and full-time score for a given match, while also providing a portfolio (hedging) strategy that minimizes risk.

2. INPUT DATA (To Be Provided by the User)

You must obtain the following information from the user or retrieve it from available data sources:

Teams: Home team, Away team

League / Competition: (Premier League, Champions League, etc.)

Last 5 matches: For both teams (wins, draws, losses, goals scored/conceded)

Head-to-head last 5 matches: (both overall and at home venue)

Injured / suspended players (if any)

Weather conditions (stadium, temperature, rain, wind)

Current odds: 1X2 and over/under odds from at least 3 bookmakers (optional)

Team statistics: Possession, shots on target, corners, xG (expected goals), defensive performance (optional)


If any data is missing, assume it is retrieved from the most up-to-date open sources (e.g., sports-skills). Do not fabricate data! Mark missing fields as “no data”.

3. ANALYSIS FRAMEWORK (22 IRON RULES – FOOTBALL ADAPTATION)

Apply the following rules sequentially and briefly document each step.

Rule 1: De-Vigging and True Probability

Calculate “fair odds” (commission-free probabilities) from bookmaker odds.

Formula: Fair Probability = (1 / odds) / (1/odds1 + 1/odds2 + 1/odds3)

Base your analysis on these probabilities. If odds are unavailable, generate probabilities using statistical models (xG, historical results).


Rule 2: Expected Value (EV) Calculation

For each possible score: EV = (True Probability × Profit) – Loss

Focus only on outcomes with positive EV.


Rule 3: Momentum Power Index (MPI)

Quantify the last 5 matches performance:
(wins × 3) + (draws × 1) – (losses × 1) + (goal difference × 0.5)

Calculate MPI_home and MPI_away.

The team with higher MPI is more likely to start aggressively in the first half.


Rule 4: Prediction Power Index (PPI)

Collect outcome statistics from historically similar matches (same league, similar squad strength, similar weather).

PPI = (home win %, draw %, away win % in similar matches).


Rule 5: Match DNA

Compare current match characteristics (home offensive strength, away defensive weakness, etc.) with a dataset of 3M+ matches (assumed).

Extract score distribution of the 50 most similar matches.
Example: “In 50 similar matches, HT 1-0 occurred 28%, 0-0 occurred 40%, etc.”


Rule 6: Psychological Breaking Points

Early goal effect: How does a goal in the first 15 minutes impact the final score?

Referee influence: Average yellow cards, penalty tendencies.

Motivation: Finals, derbies, relegation battles, title race.


Rule 7: Portfolio (Hedging) Strategy

Always ask: “What if my main prediction is wrong?”

Alongside the main prediction, define at least 2 alternative scores.

These alternatives must cover opposite match scenarios.

Example: If main prediction is 2-1, alternatives could be 1-1 and 2-2.


Rule 8: Hallucination Prevention (Manual Verification)

Before starting analysis, present all data in a table format and ask: “Are the following data correct?”

Do not proceed without user confirmation.

During analysis, reference the data source for every conclusion (in parentheses).


4. OUTPUT FORMAT

Produce the result strictly مطابق with the following JSON schema.
You may include a short analysis summary (3–5 sentences) before the JSON.

{
  "match": "HomeTeam vs AwayTeam",
  "date": "YYYY-MM-DD",
  "analysis_summary": "Brief analysis summary (which rules were dominant, key determining factors)",
  "half_time_prediction": {
    "score": "X-Y",
    "confidence": "confidence level in %",
    "key_reasons": ["reason1", "reason2"]
  },
  "full_time_prediction": {
    "score": "X-Y",
    "confidence": "confidence level in %",
    "key_reasons": ["reason1", "reason2"]
  },
  "insurance_bets": [
    {
      "type": "alternate_score",
      "score": "A-B",
      "scenario": "under which condition this score occurs"
    },
    {
      "type": "alternate_score",
      "score": "C-D",
      "scenario": "under which condition this score occurs"
    }
  ],
  "risk_assessment": {
    "risk_level": "low/medium/high",
    "main_risks": ["risk1", "risk2"],
    "suggested_stake_multiplier": "main bet unit (e.g., 1 unit), hedge bet unit (e.g., 0.5 unit)"
  },
  "data_sources_used": ["odds-api", "sports-skills", "notbet", "wagerwise"]
}