higgsfield-troubleshoot

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Use when a Higgsfield generation fails, produces poor quality, looks wrong, doesn't match the prompt, or the user needs to fix or improve an output.

AI & Automation 224 stars 47 forks Updated yesterday MIT

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Quality Score: 92/100

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78
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100
Frontmatter 20%
70
Documentation 15%
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Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Higgsfield Troubleshooting Guide ## Common Problems & Fixes ### Problem: Character face is inconsistent or morphing **Cause:** No Soul ID reference; prompt has conflicting appearance descriptions **Fix:** - Create a Soul ID reference and use it in subsequent generations - Remove any appearance descriptions that contradict each other - For image-to-video: don't re-describe the face — let the input image carry it - Use Kling 3.0 for best character consistency (or Kling 2.6 if no audio needed) --- ### Problem: Camera movement isn't working / is generic **Cause:** Camera described vaguely, not using exact preset names **Fix:** - Replace generic descriptions with exact preset names: "Dolly In", "FPV Drone", "360 Orbit" - Put the camera instruction on its own line or clearly labeled: "Camera: [name]" - Don't describe what the camera is doing in prose — name the control directly --- ### Problem: Prompt is ignored / output doesn't match **Cause:** Prompt too long, conflicting instructions, over-specified **Fix:** - Cut prompt to under 200 words — trim the least essential details (short-form prompts only; block-scaffold production briefs are a different regime — root `SKILL.md` HARD RULE 8) - Remove any contradictory elements (don't say both "moving fast" and "frozen in place") - Lead with the most important element: Subject → Action → Camera → Style - Split complex scenes into multiple separate generations --- ### Problem: Visual style looks wrong / generic **Cause:** No st...

Details

Author
OSideMedia
Repository
OSideMedia/higgsfield-ai-prompt-skill
Created
4 months ago
Last Updated
yesterday
Language
Python
License
MIT

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