ai image repair prompt doctor

    1

    Diagnose failed AI images and generate surgically precise repair prompts for Midjourney, DALL-E, and Stable Diffusion.

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    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    ai image repair prompt doctor

    Example session with this skill installed

    My prompt was 'cyberpunk street, neon signs, rainy, photorealistic' but I got a sunny day in a clean city with no neon. I want a dark, rainy, neon-drenched alley. Fix this for Midjourney.

    • Read your context and instructions
    • Compiled the ai image repair

    I have analyzed the failure of your cyberpunk prompt. The model defaulted to a standard city aesthetic because the lighting and time-of-day constraints were too vague to override the 'street' default.

    Diagnosis Report

    Summary

    The original prompt failed because 'cyberpunk' and 'neon' were treated as style tags rather than environmental constraints. The model prioritized 'street' and 'photorealistic', defaulting to daylight. We need to explicitly kill the daylight and force a dark environment.

    Intended vs Actual Comparison

    #Prompt ClaimActual ResultStatus
    1Cyberpunk streetClean modern cityBroken
    2Neon signsNone visibleAbsent
    3RainyDry pavementAbsent
    4PhotorealisticSharp, clearKept

    Failure Classification

    Claim 2 & 3 (Neon/Rain): Prompt Defect. The prompt lacked lighting hierarchy. Without 'night' or 'darkness', the model used a high-sun default.

    Preserve / Correct / Remove / Constrain

    • Preserve: Photorealistic texture.
    • Correct: Lighting (change from sunny to midnight).
    • Remove: Daylight, clean surfaces.
    • Constrain: Rain intensity and neon color frequency.

    Repair Prompt

    cyberpunk alleyway at midnight, heavy rain, puddles reflecting neon light, glowing pink and cyan signage, cinematic lighting, dark atmosphere, ultra-detailed, photorealistic --ar 16:9 --no sunlight, daytime

    Next steps

    • Run this in Midjourney v6 for better adherence to the --no parameters.
    • If the rain is too light, add weights like heavy rain::2.
    • Use a specific street-level camera angle if the composition is still too wide.

    Validation Check

    • Clarity: Unambiguous night scene.
    • Consistency: No conflicting light sources.
    • Controllability: Specific colors and time defined.
    • Completeness: Fixes rain and neon absence.
    • No regressions: Maintains photorealism.
    • Model fit: Uses Midjourney parameter syntax.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    AI image generators often ignore specific instructions, hallucinate unwanted elements, or produce anatomical errors. Developers and designers waste hours "prompt guessing" without understanding why a specific model failed to interpret their input.

    What it does

    • Deconstructs original prompts into subject, style, composition, and technical claims to find the point of failure.
    • Maps intended vs. actual results in a structured comparison table to isolate "absent" or "broken" instructions.
    • Classifies failures as either Prompt Defects or Model Limitations to prevent impossible repair attempts.
    • Generates a surgically precise repair prompt using affirmative, weighted language and negative constraints.
    • Validates the new prompt against a 6-point checklist to ensure clarity, consistency, and model controllability.

    Frameworks & tools

    Midjourney, DALL-E 3, Stable Diffusion, Flux, Adobe Firefly, and Ideogram.

    Why this beats prompting it yourself

    Instead of just adding more keywords, this skill performs a root-cause analysis. It identifies which parts of your prompt are working so you don't break them while fixing errors, and it stops you from fighting architectural model limits that a prompt cannot solve.

    Use cases

    • Fixing composition errors where the background overpowers the main subject.
    • Correcting "style bleed" where an aesthetic instruction is ignored by the model.
    • Removing unwanted subjects or artifacts without using vague negative prompts.
    • Refining lighting and color palettes when the model defaults to high-saturation presets.

    Known limitations

    Cannot fix inherent model architectural failures like finger counts or text rendering through prompting alone. Requires the original prompt, failed image, and intended outcome to function.

    Requires the original prompt text and the failed image output. Cannot bypass hard architectural model limits like exact finger counts or perfect text rendering.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Listed1 month ago

    What's inside

    Frequently Asked Questions

    This skill acts as a diagnostic tool that deconstructs your failed prompts and images to identify why the AI ignored specific instructions or produced style bleed, providing a 'surgically precise' replacement prompt to fix the error.

    Yes, the skill is engineered to work across all major platforms including Midjourney, DALL-E 3, Stable Diffusion (including Flux), Adobe Firefly, and Ideogram, adapting its repair logic to each model's specific quirks.

    You will need to provide the original prompt used, a description of the failed image (or the image itself if supported by your interface), and a clear description of what you intended the outcome to be.

    The skill identifies 'Model Limitations'—such as persistent issues with finger counts or complex text—so you know when a problem cannot be solved by prompting alone, saving you from wasting credits on impossible repairs.

    Upon purchase, you receive the full diagnostic framework, the root-cause analysis logic, and the 6-point validation checklist used to generate the final optimized prompts.

    Buyers receive access to all future version updates, ensuring the diagnostic logic remains effective as new models like DALL-E 4 or updated Midjourney versions are released.

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