Negative Prompts and Troubleshooting

Every image generator produces unwanted outputs sometimes. The difference between a frustrating session and a productive one is knowing how to diagnose what went wrong and fix it without rewriting your entire prompt.

This tutorial covers negative prompts, systematic troubleshooting, and the iterative refinement process that produces consistently good results.

What negative prompts do

Negative prompts tell the generator what to avoid in the output. They work by reducing the influence of specific concepts during the generation process. Not all generators support them explicitly (some use different mechanisms for guidance), but the underlying principle — telling the model what you don’t want — applies broadly.

Basic hygiene negatives prevent common quality problems:

text, watermark, logo, signature, blurry, low quality, low resolution, jpeg artifacts, deformed

These are worth including in every prompt as a baseline. They suppress the most common unwanted artifacts.

Style negatives steer away from unwanted aesthetic directions:

cartoon, illustration, painting, anime, 3D render, CGI

Use these when you want photorealistic output. Conversely, if you want illustration, you might negate: photograph, realistic, photographic

Content negatives suppress specific unwanted elements:

extra fingers, extra limbs, distorted face, ugly, mutated

These address known failure modes in human figure generation.

The hierarchy of prompt fixing

When an output doesn’t match your intent, resist the urge to add more negatives immediately. Follow this diagnostic hierarchy:

1. Is the subject wrong?

If the generator produced something fundamentally different from what you described, the fix is in your positive prompt, not the negative. Adding “not a cat” to the negative is less effective than making your subject description more specific in the positive prompt.

Fix: Make the subject block more specific. Add material properties, spatial context, and distinguishing details.

2. Is the composition wrong?

If the subject is right but the framing, angle, or arrangement is off, adjust your composition block.

Common composition failures and their fixes:

• Too far away: Add “close-up” or “medium shot” explicitly
• Wrong angle: Specify “eye level,” “low angle,” or “overhead” rather than assuming the generator will guess
• Too busy: Add “minimal composition,” “negative space,” or “clean background”
• Wrong orientation: Specify the aspect ratio (“portrait orientation, 2:3 aspect ratio”)

3. Is the lighting wrong?

Lighting problems are the most common issue for prompts that are otherwise well-structured. See our lighting tutorial for vocabulary.

Common lighting failures and their fixes:

• Too flat: Add directional light. “Key light from the upper left” immediately adds dimension
• Too dark: Don’t just say “bright” — specify where the light should be stronger: “well-lit subject, bright key light”
• Wrong mood: Check your light quality. Hard light = dramatic. Soft light = gentle. Change the quality, not the quantity
• Unnatural color: Specify color temperature explicitly: “neutral white studio light” or “warm golden hour light”

4. Is the style wrong?

If the technical quality, color grading, or aesthetic doesn’t match your intent, adjust the style block.

• Looks like a phone photo: Add “professional photography,” “studio lighting,” and specific camera/lens language
• Wrong color palette: Describe the grading: “desaturated cool tones” or “warm amber and teal color grade”
• Wrong era/genre: Be more specific about the look you want. “1940s film noir” is better than “vintage”

5. Persistent artifacts?

Only now should you reach for negative prompts. And be specific:

• Instead of ugly, try distorted proportions, anatomical errors
• Instead of bad quality, try jpeg compression, noise, chromatic aberration
• Instead of wrong style, try the specific style you’re seeing: oil painting, watercolor, sketch

The iterative refinement process

Professional prompt engineering is rarely one-shot. Here’s a systematic approach:

Round 1: Establish the base

Write your five-block prompt (see our anatomy tutorial). Generate 2-4 variations. Evaluate what works and what doesn’t.

Round 2: Fix the biggest problem

Identify the single biggest issue. Adjust only the relevant block. Don’t change everything at once — you won’t know what fixed the problem (or what made it worse).

Round 3: Refine details

Once the base image is solid, add refinement language: specific textures, subtle lighting adjustments, color grading fine-tuning. Small, targeted additions.

Round 4: Lock it down

Add negative prompts to suppress any remaining artifacts. Add quality modifiers to the finish block. Generate a few more variations to confirm consistency.

Generator-specific considerations

While imageprompt.com focuses on tool-agnostic techniques, different generators have different strengths and failure modes:

Prompt length sensitivity varies. Some generators respond well to long, detailed prompts. Others perform better with concise language and rely more on default behaviors. If your detailed prompt produces worse results, try condensing to the essential elements.

Negative prompt support is not universal. If your generator doesn’t support negative prompts directly, front-load the positive prompt with the most important elements (generators generally weight earlier terms more heavily) and use style-anchoring language to steer away from unwanted directions.

Seed consistency — if your generator supports seed values, use the same seed when comparing prompt adjustments. This isolates your prompt changes from random variation.

Common failure modes by subject type

Portraits

• Waxy skin: Remove “smooth” or “perfect” skin descriptors. Add “natural skin texture” or specify the lighting as less diffused
• Wrong eye direction: Specify “looking at camera,” “looking to the left,” or “eyes cast downward”
• Uncanny expressions: Describe the emotion through physical cues (“slight smile, relaxed brow”) rather than abstract terms (“happy”)

Products

• Floating in space: Add a surface description: “on a marble surface,” “resting on dark fabric”
• Wrong scale: Include a scale reference or specify the product’s actual size relative to the frame
• Label/text issues: Most generators struggle with readable text. Use “blank label” or “no visible text” and plan to add text in post-production

Landscapes

• Too generic: Add time of day, weather, and season. “Mountain landscape” is vague; “snow-capped mountain at blue hour, thin cirrus clouds, late autumn” is specific
• Unrealistic scale: Include foreground, midground, and background elements to establish depth
• HDR look: Avoid “vivid” and “colorful.” Try “natural color palette” or specify the exact color mood you want

Food

• Unappetizing colors: Specify the actual colors of the food. “Golden-brown crust” is better than “delicious bread”
• Wrong styling: Add “food styling” or “editorial food photography” to trigger professional plating associations
• Flat composition: Specify the angle. Flat lay (overhead) or three-quarter angle (“45-degree camera angle”) both produce reliable food photography framing

When to start over

Sometimes iteration won’t fix a prompt. Start fresh when:

• The generator consistently ignores a core element despite multiple rephrasing attempts
• You’ve accumulated so many additions and negatives that the prompt has become contradictory
• The style you’re targeting requires a fundamentally different approach than what you started with

Starting over with lessons learned is often faster than patching a broken prompt.

Browse our prompt posts for real-world examples of well-structured prompts, each with a “What to change if it fails” section addressing the most likely issues for that specific prompt pattern.