Stefan VaskevichGenerating clean 3D character references by hand is a friction trap. You prompt for a strict-front A-pose; the model hands you a 3/4 hero shot. You prompt the same character three times and get three slightly different faces, three slightly different palettes, three different hat angles. None of the parts fit back together when you try to assemble them in 3D.
The fix is mechanical, not artistic: lock the rules, lock the camera angle, lock the model choice, run the same regimen every time. That is exactly what a skill is for. Skills are packaged, repeatable instruction sets that an AI agent follows step-by-step — same prompts, same gates, same verifier — so the output is consistent across runs and across operators. Anthropic introduced them as a primitive earlier this year; the full primer is on anthropic.com/news/skills.
This page hands you a ready-made skill — Character Sheet Pipeline — that turns one character image into a complete production-ready 3D reference pack. Strict-front A-pose sheet, supplementary multi-view sheet, isolated parts that match the same orientation, optional side+back projections, and an optional 360° turntable. All gated, all verified, no 3/4 drift.
Download the skill
Works in Higgsfield Supercomputer, Claude Code, and Codex — plus most other agentic platforms that read skill files (ChatGPT Projects, OpenAI Agents SDK, OpenClaw, Hermes, and similar).
What you get back
One uploaded character → a structured folder you can drop directly into Tripo, Hunyuan, Rodin, Pixal3D, or any image-to-3D generator. The run below started from this single reference image of a chibi arctic-fox wizard:
The folder layout the skill writes for you:
character_pack/
00_sheet/
01a_apose_front.png # strict front, 2K (Nano Banana Pro)
01b_character_sheet.png # 16:9, 3 projections + accessories (GPT-Image-2)
parts_inventory.md
01_parts/
head_front.png # strict front, 2K
body_front.png # strict front, in-pose
hat_front.png
spellbook_front.png # one per accessory
tail_front.png
02_multiview/ # only for parts you approve at Gate 2
head_side.png
head_back.png
body_side.png
body_back.png
03_360/ # only assets you approve at Gate 3
full_character_360.mp4 # locked-camera orbit
manifest.json # parts, models, seeds, cost, retry logHow to use it
Download the archive, send it to your agent (Higgsfield Supercomputer, Claude Code, Codex, ChatGPT, the OpenAI Agents SDK, or any skill-aware tool), and ask it to install the skill. There is no per-platform setup — the agent reads SKILL.md, registers it under its skill name, and the workflow is available the next time you upload a character image and ask for a reference pack.
The cardinal rule — STRICT FRONT, never 3/4
The single hardest problem in image-to-3D pipelines isn't generating parts — it's generating parts that fit back together when modeled separately. The seams match only if every part is shot at the same camera angle as the sheet itself.
So the skill enforces one rule everywhere: every body part, every paired item, every accessory is generated at dead-front camera angle, matching the strict-front A-pose. Never "3/4 outer view", never "hero angle", never "presentable showcase". Side and back views exist — they belong to a dedicated multi-view stage, not as the default angle.
The pipeline — 8 stages, 3 gates
The skill walks through 8 stages with 3 explicit approval points so you never burn credits on something you didn't ask for:
| Stage | What happens | Model |
|---|---|---|
| 1 · Intake | Reads the uploaded image + your brief. Summarises what was detected. You confirm. | — |
| 2A · A-pose sheet | Strict-front A-pose, 2K, white background, flat light. Source of truth for every downstream part. | Nano Banana Pro |
| 2B · Multi-view sheet | Supplementary 16:9 sheet — front/side/back + accessories laid out. Visual aid only. | GPT-Image-2 |
| 3 · Gate 1 | Proposes a parts inventory. You confirm what to extract, skip, or add. | — |
| 4 · Part extraction | One strict-front image per approved part at 2K, anchored to the Stage 2A sheet. | Nano Banana Pro |
| 4.5 · Verifier | Vision classifier checks every strict-front output. Hard-fail → escalated retry. Up to 2 retries before escalating to you. | GPT-4 / GPT-5 vision |
| 5 · Gate 2 + Multi-view | Proposes which parts get side + back projections. You approve. Renders them. | Nano Banana Pro |
| 6 · Gate 3 + 360s | Quotes credit cost. You pick: all assets, full character only, or custom. Locked-camera 360° orbit per asset. | Seedance 2.0 |
| 7 · Package | Assembles the folder, writes manifest.json with seeds, costs, and the per-retry verdict log. | — |
The methodology behind it
The skill is a direct port of a 4-step manual workflow — ideation, clean sheet, parts, views — that gets shipped before any 3D modeller touches a generator. The manual version is documented in detail with a full piglet-character walkthrough and the reasoning behind each rule:
→ Read the full 4-step character reference workflowIf you've never built a reference pack manually, that piece is the better starting point — it explains why each constraint in the skill exists. The skill itself is the "press play" shortcut once those rules are familiar.
