Leonardo AI Negative Prompts: A Bounded Troubleshooting Reference
- Editorial status
- Verified
- Last verified
- 2026-07-16
- Sources
- 3 listed
On this page
Key takeaways
- Write terms, not negated sentences
- Unwanted-element diagnosis table
- Starting hypotheses by category
- One-variable troubleshooting sequence
Leonardo AI Negative Prompts: A Bounded Troubleshooting Reference
A negative prompt is a list of concepts the selected image model should make less likely. Leonardo's prompting help calls it a first defence against unwanted details and then lists changing the model, aspect ratio, or—with Alchemy—style when an element persists. It also points to Canvas for manual removal.
Input-location documentation checked: 2026-07-16. The supplied prompting article documents the negative-prompt feature but was modified on 2023-06-30. The current Image Creation article was modified on 2026-02-17, yet its text does not identify a stable negative-prompt field location. The live label or placement must therefore be confirmed in the current signed-in interface; this guide does not invent a permanent click path.
Documented: negative prompts accept unwanted details; the source lists changing the model, aspect ratio, or—with Alchemy—the style as alternatives; and Canvas provides mask/erase editing for a selected area.
Locally checked: the diagnosis table, term lists, and worksheet below were checked as text-only procedures against the supplied official articles on 2026-07-16.
Not tested: no live field-location check, generation, visual comparison, or Canvas edit was performed. No independent image-generation comparison was performed for this guide.
Write terms, not negated sentences
If a negative-prompt field is present in the signed-in interface, this worksheet uses a deliberately narrow writing convention.
Editorial convention, not vendor syntax: record comma-separated bare terms as starting hypotheses. Prefer:
extra fingers, duplicate limbs, background text
Avoid sentences built around “no” or “without,” such as no extra fingers or portrait without text. Bare terms make this editorial worksheet easier to inspect; the official source does not prescribe this syntax.
Keep the positive prompt focused on what the scene should contain. Do not place the same concept in both inputs. If red umbrella appears in the positive prompt and umbrella appears in the negative input, the instructions conflict and the worksheet cannot isolate the cause.
Boundary: explicit negative prompts do not guarantee removal. They change a model input; they are not a deletion command.
Unwanted-element diagnosis table
Both the issue-to-term and issue-to-next-variable mappings are editorial starting hypotheses.
| Observed issue | Editorial term hypothesis | What stays fixed | Editorial next-variable hypothesis |
|---|---|---|---|
| Extra hand or digit | extra fingers, duplicate hands | Positive prompt, model, dimensions, style | Model |
| Duplicate subject | duplicate person, cloned subject | Positive prompt, model, dimensions, style | Aspect ratio |
| Unrequested lettering | letters, captions, watermark | Positive prompt, model, dimensions, style | Style |
| Background object | Name the object directly, such as street sign | Positive prompt, model, dimensions, style | Canvas mask or erase |
| Soft or noisy region | blur, noise | Positive prompt, model, dimensions, style | Model |
The terms are diagnostic inputs, not claims about expected output. Record the observed issue in plain language before choosing a term. Broad lists make it harder to know which concept affected the next run.
Starting hypotheses by category
These deliberately small lists are starting hypotheses, not universal presets.
- Anatomy:
extra fingers,duplicate limbs,asymmetrical eyes - Composition:
cropped subject,duplicate person,cluttered background - Surface artifacts:
watermark,letters,compression artifacts - Focus:
blur,soft focus,motion streaks
Start with one or two terms that name the observed problem. Add another term only after recording what changed. A category label such as “bad quality” is less diagnosable than the visible element compression artifacts.
One-variable troubleshooting sequence
This sequence is an editorial experiment design created for reproducibility. The prompting source lists model, aspect ratio, and—with Alchemy—style as unordered alternatives when an unwanted element persists; it does not prescribe a sequence. The worksheet imposes the following progression so only one recorded variable changes at a time:
- Negative prompt: add one precise unwanted term. Keep the positive prompt, model, aspect ratio, and style fixed.
- Model: if the element persists, restore the previous negative input and change only the exact model selection. Use the Leonardo model-selection reference to record the model and remember that settings vary by model.
- Aspect ratio: return to the recorded model state and change only the visible aspect-ratio control.
- Style: return to the recorded aspect ratio and, with Alchemy and when the selected model exposes the control, change only the style. Otherwise record this step as not applicable.
- Canvas: if the unwanted element remains localized, open Canvas, place the generation frame over the area, then choose Draw Mask for a change that retains underlying information or Erase for removal before replacement.
Do not change all five variables in one attempt. A multi-variable change cannot show which control was associated with the difference.
Text-only troubleshooting worksheet
The following example is reproducible as a record review; it does not require an image run.
Positive prompt
studio portrait of one violinist, plain grey background, waist-up framing
| Step | Negative input | Model | Aspect ratio | Style | Canvas action | Interpretation |
|---|---|---|---|---|---|---|
| Baseline | empty | record exact label | record visible value | record visible state | none | Describe the unwanted element |
| 1 | duplicate hands | same | same | same | none | Negative input is the only changed field |
| 2 | same as step 1 | one recorded alternative | same | same | none | Model is the only changed field |
| 3 | same as step 1 | restore baseline | one alternative | same | none | Aspect ratio is the only changed field |
| 4 | same as step 1 | baseline | baseline | one Alchemy style alternative, if applicable | none | Style is the only changed field |
| 5 | unchanged | baseline | baseline | baseline | mask or erase named area | Local edit is separated from generation controls |
Before using this worksheet, replace every “record” placeholder with the values visible in the signed-in interface. If the chosen model hides the style control, mark it not shown for selected model rather than carrying over a value.
Canvas boundary
The Canvas article says the generation frame limits where Canvas generates while unlocked. Draw Mask paints an area to change while retaining some information beneath it. Erase removes the selected area before a prompted replacement. Those operations are local edits, not proof that a negative prompt failed generally.
Use Canvas only after the generation-variable record is complete. Save the action as a separate worksheet row so the generated input and the manual edit are not conflated.
Primary sources
- Prompting Tips & Tricks — official prompting article, modified 2023-06-30; negative-prompt purpose; model, aspect-ratio, and—with Alchemy—style alternatives; and the Canvas fallback.
- How to Generate Images with Leonardo.Ai — official current-interface article, modified 2026-02-17; Image Creation access and model-dependent controls.
- How To Use Canvas Editor Tool — official Canvas article, modified 2026-02-18; generation frame, Draw Mask, Erase, and prompted regeneration.
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