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ai image rescue and repair
Systematically diagnose and repair failed AI image prompts while preserving successful elements.
$5
Works with the AI Agents you already use
ai image rescue and repair
Example session with this skill installed
My prompt 'a cozy library with a fireplace and a cat sleeping on the rug' failed. The cat has 6 toes, the books look great, and the lighting is perfect, but the fireplace is way too small.
- Read your context and instructions
- Compiled the ai image rescue
I have analyzed the failure. The primary issues are a scale conflict (fireplace) and a morphological artifact (cat's paws), while the environmental assets and lighting are successful.
Diagnosis
- Failure class: Multi-type (Composition + Artifact)
- Root cause: Under-specification of fireplace dimensions and model artifacting on paws.
- Working elements (LOCK): cozy library, warm lighting, books on shelves, cat asleep.
- Broken elements (REPAIR): fireplace size (too small), cat paw anatomy (6 toes).
- Uncertain fragments: None.
Rescue Prompt
a cozy library with a fireplace and a cat sleeping on the rug, warm lighting, tall wooden bookshelves filled with books, a large stone fireplace centered on the back wall, fireplace occupies at least one-third of the frame, logs burning with visible flames, cat with natural paw anatomy, exactly 5 toes per paw, ensure all other aspects remain unchanged.
--no six toes, extra toes, tiny fireplace, bare wall, distorted paws
Test Result
Waiting for generation. Please provide a description of the new image once rendered.
Evaluation
| LOCK preserved? | REPAIR fixed? | New issues? |
|---|---|---|
| All preserved | TBD | TBD |
Next Step
- Run the prompt above.
- If the fireplace is corrected but the cat still has issues, I will refine only the cat fragment.
- If the image is perfect, we will finalize.
Connects securely to your tools. The creator never sees your data.
About this skill
The problem
Rewriting prompts from scratch when an AI image fails often destroys the parts you liked. You lose the composition or lighting while trying to fix a single artifact or a misspelled word.
What it does
- Decomposes failed prompts into "LOCK" and "REPAIR" semantic units to protect working elements.
- Classifies failures by type including composition, identity, product accuracy, and artifacts.
- Generates targeted rescue prompts using precise corrective syntax and negative descriptors.
- Executes a controlled iteration loop that applies minimal deltas to reach the goal.
- Evaluates retest results using a structured matrix to prevent regressions.
Why this beats prompting it yourself
Manually tweaking prompts often leads to "prompt drift" where fixing one issue introduces three new ones. This skill uses a systematic diagnostic workflow to isolate variables, ensuring you only change the specific fragments causing the failure while maintaining visual consistency.
Use cases
- Fixing distorted limbs or extra fingers in character portraits.
- Correcting misspelled text on signs or product packaging.
- Scaling architectural elements like fireplaces or windows without altering the room layout.
- Adjusting specific lighting directions while preserving existing art styles.
Known limitations
Requires the user to provide the original prompt and a description of the failure. Limited to 5 iterations per rescue session.
Requires the original prompt and a description/image of the failure. Hard limit of 5 iterations per session to prevent infinite loops.
How to use
- 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
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 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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