Higgsfield Pipeline

Higgsfield Production Pipeline

QUICK FACTS

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

• 8-stage Master Chain: Popcorn → Seedream/Soul → Animate → Recast → Lipsync → Vibe Motion → Upscale → Assemble; most good short-form uses 3–5 stages [→](#the-master-production-chain)
• Lock 9 project fields before touching any tool; "what must stay consistent" is the load-bearing one [→](#step-01-start-with-the-project-not-the-prompt)
• One job per scene — six scene purposes; a good scene prompt answers six questions [→](#step-06-give-every-scene-one-job)
• 7 reusable prompt-module types: character identity, camera, lighting, style, motion, negative prompt, continuity [→](#step-07-use-prompt-modules)
• 80% rule: keep what worked, fix only the mistake; every diagnosed failure becomes a new negative rule [→](#step-0809-fix-failures-protect-what-worked)
• Build in 8 passes: Concept → Project script → Scene breakdown → Shot list → Image prompts → Video prompts → Review → Fix [→](#step-10-build-the-project-in-passes)
• Use the EXACT same character description (copy-paste) in every Popcorn prompt — continuity without Soul ID [→](#stage-1-storyboard-with-popcorn)
• Seedream edits the image, not the video — always edit the Hero Frame before animating, never after [→](#stage-2-image-editing-with-seedream)
• Model by scene type: Sora 2 for stunts/epic ("one continuous shot, no cuts"), Kling 2.6 portraits, Seedance quiet interiors [→](#stage-3-animate-by-scene-type)
• Recast swaps identity while preserving motion, camera, and lighting; the "prompt" is the reference image you upload [→](#stage-4-recast-character-swap)
• Audio routing: existing video + speech → Lipsync Studio; new content with audio → Kling 3.0; talking head → Kling Avatars 2.0 [→](#stage-5-lipsync-audio)
• Higgsfield has no native timeline editor — assemble in DaVinci Resolve / Premiere / CapCut [→](#stage-8-assembly)
• Pipeline E hard rules: 15-second cap per scene, one generation per style, feed the previous scene's video as continuity reference [→](#stage-5-seedance-20-with-keyframe-previous-video)
• Soul Cinema keyframes: deliberately short 5–15 word prompts with enhancer ON — long prompts starve the enhancer [→](#stage-1-soul-cinema-keyframe-style-first-enhancer-on)
• Never describe character age in Seedance prompts; >15s per scene degrades prompt adherence — split the scene [→](#pipeline-e-pitfalls)
• Draw a top-down schema when 2+ characters, a key prop placement, or complex camera geometry — prompt in absolute terms ("A 2m from B") [→](#spatial-blocking-top-down-schema-for-multi-character-scenes)
• Never animate a "good enough" image; if the character looks wrong in the Hero Frame, Recast is the fix — not the animation prompt [→](#pipeline-pitfalls)

The Core Insight

Every Higgsfield tool is strong individually. The real power is when you chain them. A professional result almost always involves at least 3 tools in sequence. This skill documents the key chains and how to prompt for each stage.

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Building Complete AI Projects — The 10-Step Methodology

The Core Insight above answers why you chain tools. The next question is how to plan the project before any tool is touched. Most people skip planning and start prompting straight from a creative impulse — a generation here, a clip there, hoping the pieces will connect. They don't. A project that's planned at the script and bible level lands consistently; a project assembled prompt-by-prompt drifts on character, style, and continuity within three or four generations.

This section documents a 10-step methodology for building complete AI projects — from idea through finished sequence — that sits upstream of the Master Production Chain below. Use these 10 Steps as a planning discipline; use Pipelines A-E to execute the tool-level chain once your project plan is locked. The closing § Simple Workflow gives the imperative-action version of the same 10 Steps if you want the execution recipe before the principles.

Step 01 — Start With the Project, Not the Prompt

Before writing a single prompt, define what you are building. The AI cannot read your intent; if you skip this step the model fills in the gaps with whatever the prompt happens to suggest, and the project drifts within the first few generations.

Lock these nine fields before any tool is touched:

• Project type
• Main subject
• Visual style
• Scene goal
• Audience
• Mood
• Length
• Setting
• What must stay consistent

The last field is the load-bearing one. If you don't know what must stay consistent across the project, every other field can be locked and the result will still feel disjointed.

Step 02 — Build a Master Script

A Master Script is the project blueprint — the single document that keeps every scene connected to the same goal. It does not have to be a Hollywood screenplay; it just needs to explain the full idea clearly.

> Master Script disambiguation. "Master Script" in this > context means the structured project document, not a screenplay. > The source explicitly notes "it does not have to be a Hollywood > screenplay; it just needs to explain the full idea clearly." > This is distinct from Hollywood screenplay craft (slug lines, > action lines, character cues, transitions) — that's a different > discipline and is not in this skill's scope.

The Master Script should include:

• The story or concept
• The scene order
• The main characters or products
• The visual style
• The camera rules
• The setting
• The emotional tone
• The continuity rules
• What should never happen

Without a Master Script, each prompt becomes its own random island. With one, every prompt belongs to the same project — characters carry between scenes, the visual style holds, and the negative rules ("what should never happen") stay out of the output.

Step 03 — Use GPT as Your Creative Assistant

Do not use GPT like a magic button. Use it like a creative team member. GPT plays five distinct roles in the project pipeline:

• Concept Builder — turns a rough idea into a structured

concept

• Script Writer — drafts the Master Script from the concept
• Shot List Planner — breaks the script into scene-by-scene

shot lists

• Prompt Refiner — turns each shot into image or video prompt

text

• Problem Solver — diagnoses failed generations and rewrites

the offending prompt

The key is staging. Do not ask GPT to do everything at once. Ask for the project structure first. Then the scenes. Then the prompts. Then the revisions. The output quality at every stage depends on the input quality of the prior stage; cascading the work in order gives you control over each handoff.

> In-platform alternative. Higgsfield has an in-platform GPT-5 > copilot (Higgsfield Assist at higgsfield.ai/chat) trained > specifically on Higgsfield's tools and workflows. For quick > in-platform prompt generation and platform-navigation questions, > see ../higgsfield-assist/SKILL.md. For upstream project > staging across multiple sessions, an external GPT (Claude, > ChatGPT) running this 10-step methodology is the better fit > because state carries across the full project, not just the > current platform session.

Step 04 — Separate the Script From the Prompt

The script is what happens. The prompt is how the AI shows it. These are two different artifacts that serve two different purposes — keep them in separate documents, and don't let prompt-shaped instructions leak into the script.

A script line might read:

> "She walks into the room and realizes something is wrong."

The same beat, as a prompt, reads:

> "A woman slowly enters a dim apartment from the hallway. Camera > stays in front of her at chest height, tracking backward as she > steps forward. Her eyes move toward an overturned chair and > broken lamp. Warm hallway light behind her, cold blue window > light across the room. Her face tightens as she realizes > something is wrong."

The prompt decomposes the beat into four production-instruction categories:

• Camera Notes — wide shot, eye-level, shallow depth of field,

focus on subject's expression

• Lighting Direction — dim, cinematic, cool blue ambient from

window, single warm lamp in corner

• Subject Movement — slow, hesitant walk, pauses mid-step,

tense posture, hand to mouth

• Environment Detail — cluttered, atmospheric, dust motes,

shadows in corners, sense of foreboding

The script gives story. The prompt gives visual instructions. You need both, in separate documents, with the script feeding the prompt rather than collapsing into it.

> Separation rule axis distinction. This is the project-level > separation — script (story) from prompt (AI instruction). For > the prompt-level separation within a single shot — Identity (who > is in frame) from Motion (what they do and how the camera moves) > — see ../higgsfield-prompt/SKILL.md § Identity vs. Motion > Separation Rule and ../higgsfield-soul/SKILL.md § Identity vs. > Motion Separation. Different axes of the same overall > composition problem; both apply.

Step 05 — Create a Project Bible

A Project Bible is a single document that locks in the rules of the project — character appearance, environment, style, what must stay consistent, what must never appear. It is especially important for any project with multiple scenes, because consistency comes from repetition and clear rules, not from the AI inferring intent.

The Project Bible should lock in:

• Character appearance
• Wardrobe
• Hair
• Color palette
• Location
• Lighting style
• Camera style
• Tone
• Props
• Negative rules
• Continuity rules

Three rules of thumb make a Project Bible work in practice:

• If your character is supposed to look the same every time,

describe them the same way every time.

• If your product is the focus, make sure the product stays the

focus.

• If your scene takes place in one location, do not let the AI

redesign the room every shot.

> Project Bible as upstream source-of-truth. The Project Bible > lives in your own files alongside the Master Script — it's the > document you maintain across the project. Two common downstream > realizations of the Bible inside Higgsfield: (i) the Character > section feeds into a Soul ID character sheet, see > ../higgsfield-soul/SKILL.md § Character Sheet Creation for the > multi-angle reference approach; (ii) Characters, Locations, and > Props feed into Cinema Studio's @ Elements system, see > ../higgsfield-cinema/SKILL.md § Elements System for the > @CharacterName / @LocationName / @PropName workflow. The > Bible is the upstream artifact; the Soul ID sheet and Cinema > Studio Elements are tool-side realizations of it.

Step 06 — Give Every Scene One Job

Every scene should have one clear purpose. When you try to make one scene do too much, the AI starts blending details — messy motion, wrong angles, extra people, broken hands, missing objects, confusing results. Six scene purposes cover most project work:

• Introduce the character
• Show the location
• Build tension
• Reveal the product
• Create emotion
• Deliver the action

A good scene prompt answers six questions:

• Who is in the shot?
• Where is the camera?
• What is the subject doing?
• What should the viewer notice first?
• What must stay visible?
• What should not happen?

Clarity wins.

> Per-shot action-count rule. Step 06 addresses the > narrative purpose of a scene (which may span multiple shots). > For the per-shot action-count rule — one primary action per > clip, with one or two secondary actions max — see > ../higgsfield-prompt/SKILL.md § One Action Per Scene. Both > useful, at different units of decomposition.

Step 07 — Use Prompt Modules

A prompt module is a reusable block of instruction. Instead of rewriting the same camera or lighting notes every time, build modules you can copy and paste. Seven module types cover most project work:

• Character identity block
• Camera block
• Lighting block
• Style block
• Motion block
• Negative prompt block
• Continuity block

Example camera block:

> "Camera stays in front of the main subject, facing them > directly while tracking backward. The subject moves toward > camera. Background movement stays behind the subject. Do not > reverse the direction."

That one block can save multiple generations. Build your own library of modules — it saves time and keeps your project stable.

> Prompt Modules as finer-grained sibling of Identity/Motion. > The 7-module taxonomy is a finer-grained sibling of the > Identity-vs-Motion separation rule used in single-shot prompts. > For Soul ID single-shot work, the 2-block separation in > ../higgsfield-soul/SKILL.md § Identity vs. Motion Separation > (also ../higgsfield-prompt/SKILL.md § Identity vs. Motion > Separation Rule) is sufficient — "Character identity block" > here aliases their "Identity Block." The 7-module taxonomy adds > a layer for multi-shot projects where camera, lighting, and > style each warrant their own reusable block.

Step 08+09 — Fix Failures + Protect What Worked

When a generation fails, do not just say "make it better" — that's not actionable. Tell GPT exactly what went wrong: which specific element is off, what to keep, what to change. Every failure should become a new rule: each diagnosed mistake gets locked into the project's negative-rules list so it doesn't recur.

When fixing, protect what already worked. If 80% of the generation was right, keep that 80%. Only fix the broken part. A lot of people destroy good prompts by changing too much — keep the subject, keep the style, keep the camera if it worked, keep the lighting if it worked. Fix only the mistake.

> Full iteration discipline lives elsewhere. The full > Change-One-Variable-at-a-Time discipline and the 6-Pass > Diagnostic Sequence (Subject / Action / Camera / Style / Audio > / Output) for when you don't yet know what's wrong are > documented in ../higgsfield-prompt/SKILL.md § The Iteration > Rule — Change One Variable at a Time. Step 08+09 here names the > three rhetorical handles ("make it better" anti-pattern, 80% > rule, "every failure should become a new rule" framing); the > mechanics live there.

Step 10 — Build the Project in Passes

Do not try to do everything at once. Build the project in clear passes:

• Pass 1: Concept
• Pass 2: Project script
• Pass 3: Scene breakdown
• Pass 4: Shot list
• Pass 5: Image prompts
• Pass 6: Video prompts
• Pass 7: Review results
• Pass 8: Fix and finalize

Each pass produces an artifact the next pass consumes. Pass 1 gives Pass 2 a concept to script; Pass 2 gives Pass 3 a script to break into scenes; and so on. AI moves fast, but fast without structure creates chaos — a workflow keeps it clean.

> Tool-level instantiation. Passes 5-7 (image prompts / video > prompts / generate) are where the Higgsfield tool chain enters > the workflow — see § The Master Production Chain below for the > 8-stage tool-level chain (Popcorn → Seedream/Soul → Animate → > Recast → Lipsync → Vibe Motion → Upscale → Assemble), and § > Pipeline Decision Guide below for the chain choice by project > type (Cinematic Short Film, Social Series, Product Campaign, > Fast Iteration, Multi-Style Short Film).

Simple Workflow — Execution Recipe

The 10 Steps above are the methodology. The Simple Workflow below is the imperative-action recipe — the same workflow expressed as steps you take in order:

1. Write the project idea.
2. Ask GPT to turn it into a project brief.
3. Ask GPT to break it into scenes.
4. Ask GPT to write a clean script.
5. Ask GPT to turn each scene into image prompts.
6. Ask GPT to turn each scene into video prompts.
7. Generate inside Higgsfield.
8. Review what worked and what failed.
9. Give GPT specific correction notes.
10. Regenerate only what needs fixing.

That is h

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: OSideMedia
• Source: OSideMedia/higgsfield-ai-prompt-skill
• License: MIT
• Homepage: https://higgsfield.ai

Install and usage instructions live in the source repository linked above.