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/higgsfield-troubleshoot

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.

From plugin
higgsfield-ai-prompt-skill
27632 skills2 commands
Install
$ npx -y skills add OSideMedia/higgsfield-ai-prompt-skill --skill higgsfield-troubleshoot --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/higgsfield-troubleshoot

Context preview

The summary Claude sees to decide when to auto-load this skill.

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.

SKILL.md

higgsfield-troubleshoot.SKILL.md
name: higgsfield-troubleshoot
description: >
  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.
user-invocable: true
metadata:
  tags: [higgsfield, troubleshoot, fix, quality, failure, improve]
  version: 3.2.0
  updated: 2026-08-09
  parent: higgsfield

Higgsfield Troubleshooting Guide

QUICK FACTS

*Generated-checked block (scripts/build_index.py verifies anchors). Read the linked sections for full context — these lines are routing aids, not the rules themselves.*

  • Face inconsistency, dead camera moves, ignored prompts, static i2v, blocked dark content — the per-problem fix list [→](#common-problems-fixes)
  • Kling 3.0 Motion Control failures are almost always upstream of the prompt: reference clip, character image, or orientation/scene-source settings [→](#motion-control-failures-kling-30)
  • Pre-generation checklist: subject, action, named camera preset, style, grade, aspect, <200 words (short-form regime) [→](#pre-generation-checklist)
  • Seedance/Cinema Studio symptom table + diagnostic flowchart: blurry = overspecified; chaotic camera = One-Move Rule violated; wrong character = prompt re-describes the reference [→](#cinema-studio-30-seedance-20-diagnostic-tree)
  • Every delivered take gets ONE of five verdicts before anything re-fires: keep / fix-in-post / edit / re-roll / rewrite [→](#take-triage-five-verdicts-for-a-delivered-take)
  • Two takes with the same flaw = rewrite, by rule; different flaws per roll = stochastic → batch-and-cull, not rewrite [→](#take-triage-five-verdicts-for-a-delivered-take)
  • Re-roll = same prompt again, unchanged — no seed parameter on this surface; every roll is a fresh sample [→](#take-triage-five-verdicts-for-a-delivered-take)
  • Change exactly one variable between takes so causality stays readable [→](#one-variable-per-retake)
  • Declare the take budget AND a written "good enough" bar before take one; half-budget with no progress forces a strategy change [→](#attempt-budget-declared-before-take-one-heuristic)
  • The shot log is the ledger row — one line per take, changed variable in `notes` [→](#the-shot-log-is-the-ledger-row)
  • Continuation/extension defects: 12-row symptom → cause → single-repair-variable atlas (planned-vs-observed opening, motion-vector drop, prop contradictions, chain-depth drift…) [→](#sequence-continuation-failure-atlas)
  • Retry Ladder: 4 terminating rungs — re-run once verbatim → treat 2nd failure as over-packing → switch model for that shot → stop after 3 paid attempts with named options [→](#retry-ladder-a-failed-take-edits-the-plan-not-just-the-dice)
  • Log EVERY confirmed fix to learning memory, and check memory first before troubleshooting [→](#log-the-outcome-always)
  • Vision-grounded diagnosis (stills only): vision proposes the `reject_reason`, the human confirms — advisory until a class clears the agreement gate [→](#vision-grounded-diagnosis-classify-the-rejected-still-dont-guess)

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 style specified, or style description too vague **Fix:**

  • Add one of the named styles: Cinematic / VHS / Super 8MM / Anamorphic / Abstract
  • Add a specific color grade description: "cold teal and orange", "warm golden amber"
  • Specify aspect ratio: 16:9 / 9:16 / 2.35:1
  • Add lighting: "golden hour", "neon", "practical only", "overcast"

---

Problem: Motion preset effect isn't visible

**Cause:** Preset not explicitly named, or scene context doesn't support the effect **Fix:**

  • Name the preset exactly as it appears in the library: "Apply Explosion preset"
  • Place the preset instruction at the end of the prompt, clearly labeled
  • Make sure the scene context supports the preset — e.g., Animalization needs a subject

who can logically transform

---

Problem: Image-to-video barely moves / is static

**Cause:** Prompt re-describes the static elements instead of what should animate **Fix:**

  • Only describe what **changes or moves** — not what is already visible in the image
  • Add an explicit camera movement: "Camera: Dolly In" or "Camera: slow Arc"
  • Specify the motion type: "hair gently lifts", "eyes blink", "she turns slowly left"
  • Add atmospheric motion: "dust floats upward", "light flickers", "steam rises"

---

Problem: VFX preset looks too artificial / cartoonish

**Cause:** Wrong model for the preset, or prompt style conflicts with effect **Fix:**

  • For grounded presets (Explosion, Freezing): use Kling 3.0 or 2.6 for realism
  • For stylized presets (Animalization, Multiverse): use Wan 2
Read more
Ships withhiggsfield-ai-prompt-skill

A comprehensive Claude skill library for generating high-quality prompts on Higgsfield AI — the cinematic video and image generation platform.

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Repo: OSideMedia/higgsfield-ai-prompt-skill