Seedance 2.0 Content Filter Guide: How to Get Your Prompts Approved

"Your content did not pass the review."

If you've used Seedance 2.0 for more than 10 minutes, you've seen this message. Probably more than once. Probably on a prompt you thought was completely harmless.

You're not the only one running into this. The safety filters are strict right now, stricter than most AI video generators. That's intentional. But it means you need to adjust how you write prompts, and nobody really explains how. This guide does. We've collected what works and what doesn't from thousands of community generations.

TL;DR

• Describe characters by visual appearance instead of using names. This alone fixes most rejections.
• Replace violent or aggressive words with cinematic alternatives ("intense power confrontation" instead of "fight").
• Keep individual scenes to 10-15 seconds and break complex sequences into 3 separate shots.
• Retry the same prompt once. The filter has a probabilistic element, and second attempts often pass.
• Add "No spoken dialogue" to silent scenes to avoid triggering voice-related filters.

Why prompts get rejected

It helps to understand what's actually going on before trying to fix it.

Seedance 2.0 runs multiple detection layers. Text analysis catches banned word combinations. Visual matching scans reference images for copyrighted characters. A real-time classifier evaluates the overall intent of your request. Industry reporting confirms these restrictions were tightened after copyright concerns from rights holders, including the Motion Picture Association.

The filter is calibrated to catch three categories:

Some rejections fall cleanly into one category. Others sit in gray areas where the classifier isn't confident, so it blocks to be safe. That's why the same prompt sometimes passes on retry: the probabilistic scoring lands differently each time.

Describe characters by appearance, not by name

If you only take one thing from this article, make it this.

The filter scans for named characters, fictional and real. Typing "Iron Man" or "Harry Potter" triggers an instant block. But describing the visual traits of an original character who shares some aesthetic qualities? That passes.

Replace every character name with a detailed physical description. Height, build, hair color, clothing, facial features, accessories. More detail means the model has more to work with and the filter has less to flag.

One thing people miss: even if you avoid the name in your text prompt, uploading a reference image of a copyrighted character still gets caught. The visual matching layer runs separately from text analysis. Use original images or AI-generated portraits instead.

This works because the filter primarily pattern-matches on explicit identifiers. "A man in red-and-blue spandex" is vague enough to pass. "Spider-Man" is not. And the description actually gives the model better instructions anyway.

Use cinematic language for action scenes

Action scenes are the second most common rejection reason. Words like "fight," "kill," "battle," "blood," "attack," and "destroy" raise flags, even in obviously fictional contexts.

Think about it this way: write like a film director describing shots, not like a novelist writing a fight scene.

Here's a word-swap table we've put together from community testing:

In practice, here's the difference:

Rejected:

Approved:

Same visual. Different framing. The approved version treats the scene as spectacle rather than violence.

One more thing worth knowing: mixing registers kills your approval rate. If 90% of your prompt uses cinematic language but you drop one graphic word in the middle, it can still trigger rejection. Keep the entire prompt in the same tone.

Structure scenes for higher approval rates

Prompt structure matters as much as word choice. Long prompts with multiple characters and multiple actions give the filter more to scan and more chances to flag something. Shorter, focused prompts pass more reliably.

Three things that consistently help:

Keep scenes short. 10-15 seconds of described action. One subject, one motion, one camera movement. If you need a 60-second sequence, generate four clips and chain them using last-frame-to-first-frame mode.

Split complex scenes into separate shots. Instead of describing an entire chase sequence in one prompt:

• Shot 1: "Wide establishing shot, a figure sprints down a rain-soaked alley, camera tracking from above"
• Shot 2: "Close-up of boots splashing through puddles, streetlight reflections rippling"
• Shot 3: "The figure emerges into a brightly lit plaza, camera pulls back to reveal the cityscape"

Each shot is simple enough that the filter processes it without issue.

Add context signals. These phrases help the classifier read your intent correctly:

• "No spoken dialogue" for silent scenes (prevents voice-related triggers)
• "Cinematic atmosphere" or "film-like composition" (signals artistic context)
• "Visual storytelling" (frames the generation as creative work)

Prompt checklist

Run through this before you hit generate:

If your prompt passes all six checks and still gets rejected, submit the exact same prompt again. This sounds weird, but the filter includes probabilistic elements. Community members report roughly 30-40% success on immediate retries for borderline prompts.

What doesn't work (save your credits)

A few things people try that don't actually help:

Misspelling character names. "Sp1der-Man" or "Ir0n Man" won't get past the filter. It uses fuzzy matching and semantic analysis, not exact string matching.

Adding disclaimers. "This is for educational purposes only" or "I own the rights to this character" has zero effect on how the filter evaluates your prompt. These statements get ignored entirely.

Burying flagged content in long prompts. The filter doesn't care about prompt length. A banned term in a 500-word prompt triggers the same response as one in a 10-word prompt.

Using heavy metaphor for prohibited content. The classifier evaluates meaning, not just keywords. Euphemistic descriptions of restricted content still get caught.

The prompt library is coming

We're building a community prompt library: a searchable collection of tested, approved prompts organized by genre and style. Action scenes, character animations, landscape shots, product videos.

Each prompt will include the exact text that passed, the generation settings used (model, aspect ratio, duration), an output preview, and tags for browsing. It'll live inside Seedance Studio. We'll announce the launch on our blog and Discord.

FAQ

Why does the same prompt sometimes pass and sometimes fail?

The content filter scores prompts probabilistically, not as a binary pass/fail. Each run can produce slightly different confidence scores. If your prompt sits near the threshold, it might pass one time and fail the next. Retrying once is a real strategy, not a workaround.

Can I use reference images of real people?

No. Seedance 2.0 blocks generation from photos of identifiable real people: celebrities, politicians, any recognizable public figure. Use AI-generated portraits or illustrated character references instead.

How do I create action scenes without getting blocked?

Swap every violent word for a cinematic one. "Two warriors in an intense power confrontation with dramatic energy clashes" produces visually similar results to "two warriors fighting" but passes the filter. Think spectacle, light, and movement rather than impact and injury.

Will the filters get less strict over time?

The system is evolving. As we collect more data on false positives, the filters will get more accurate, meaning fewer false rejections on legitimate creative content. But restrictions on copyrighted characters and real people are permanent.

I've tried everything and my prompt still gets rejected. Now what?

Remove one element at a time to isolate the trigger. Strip the prompt to its simplest version, then add details back gradually. If a specific concept keeps failing, try describing the feeling of the scene instead of the specific action. Approach it from a completely different angle.

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The filters are strict. That's where things stand. But here's something we've noticed: the constraints tend to push prompts in a better direction. More descriptive. More visual. More cinematic. The people getting the best results from Seedance 2.0 aren't fighting the filter. They're writing prompts that work with it.

Try seedance 2.0 prompt generator to create filter-friendly prompts in seconds!