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AI Anatomy Drawing Prompts

A curated bundle of the three most-starred GitHub resources that teach AI agents to draw human anatomy, skeletons, and animals without hallucinating extra fingers, fused limbs, mutated faces, or impossible proportions.

Each pick is vendored into this repo as a git subtree under skills/ so the full source — prompts, skill files, examples, license, history — travels with this repo and can be updated cleanly from upstream.


Why this exists

"Bad anatomy" is the single most common failure mode of generative image models: six-fingered hands, two-jointed elbows, mirrored faces, vestigial limbs, animals with the wrong number of legs. Three communities on GitHub have published the most-cited countermeasures:

  1. A negative-prompt vocabulary that names every anatomical failure mode so the sampler steers away from them.
  2. An agentic skill (Claude Code / Codex / OpenClaw) that wraps a curated prompt gallery, parameter best-practices, and a CLI — so the model is given structure instead of a blank canvas.
  3. A prompt cookbook for OpenAI's GPT-Image-2 that pairs every example with the actual rendered output, reference-image anchoring, and explicit "Avoid" clauses so identity and proportions stay intact across edits.

Together they cover the three layers of the stack: what to forbid (negatives), how to ask (skill scaffolding), and what good looks like (reference gallery).


The three picks

# Repo Stars Why it made the cut
1 EvoLinkAI/awesome-gpt-image-2-API-and-Prompts ~15.6k The largest curated gallery of GPT-Image-2 prompts with paired output images, including portrait, character, and figure cases that lean hard on reference-image anchoring + explicit "Avoid: extra fingers, deformed hands, warped face" clauses.
2 wuyoscar/GPT-Image2-Skill ~2.4k The top-ranked agentic skill (Claude Code / Codex / OpenClaw) for image generation. Ships a SKILL.md, CLI, parameter cheatsheets, and a deliberately small, high-signal gallery covering character design, figure illustration, and animal subjects.
3 mikhail-bot/stable-diffusion-negative-prompts ~90 The most-direct match for the brief: a battle-tested vocabulary of negative prompts (bad anatomy, mutated hands, extra fingers, fused fingers, missing limbs, long neck, malformed limbs, disfigured, cloned face) that ships with every modern SD-style stack. Small star count, outsized influence — these tokens are copy-pasted into millions of generations.

Each lives under skills/<name>/.


1. awesome-gpt-image-2-API-and-Prompts — the reference gallery

Location: skills/awesome-gpt-image-2-API-and-Prompts/ Upstream: https://github.com/EvoLinkAI/awesome-gpt-image-2-API-and-Prompts License: CC0 1.0

What it gives you

  • 583+ curated prompt cases organised by use case (portrait, character design, poster & illustration, e-commerce, ad creative, UI mockups).
  • For every case: the exact prompt, the rendered output, and (where relevant) an "Avoid" section listing the anatomical failures the prompt is engineered to suppress.
  • API usage patterns for /v1/images/generations and the multi-turn editing flow that lets you keep a subject's face/proportions stable across iterations.
  • 11 language localisations of the README.

Anti-hallucination techniques it teaches

Technique Example clause
Reference-image anchoring "use the uploaded photo as main reference; preserve the exact facial features"
Negative phrasing inside positive prompts "Avoid: extra fingers, deformed hands, warped face"
Identity locking across edits "Do not alter my facial features, only change the background"
Visual over-specification dense descriptors that leave no anatomical detail for the model to guess
Output verification every prompt is published next to its real generated image, so users can compare expected vs. actual anatomy before reusing the prompt

⚠️ The authors caution against using outputs as-is in academic figures — always validate anatomy against ground truth.

Best for

Browsing for a known visual style and lifting the negative/avoid clauses verbatim into your own pipeline.


2. GPT-Image2-Skill — the agentic skill

Location: skills/GPT-Image2-Skill/ Upstream: https://github.com/wuyoscar/GPT-Image2-Skill License: MIT

What it gives you

  • A complete agent skill folder (skills/gpt-image/) ready to drop into Claude Code, Codex ($skill-installer), OpenClaw, or Hermes Agent.
  • A gpt-image CLI for batch generation/editing with the OpenAI API.
  • Markdown reference guides covering parameter semantics (size, quality, n, format), OpenAI's official prompting best-practices, and a per-domain craft checklist.
  • A curated (intentionally small) gallery: character design, figure illustration, pixel-art creatures, and photorealistic wildlife.

Anti-hallucination techniques it teaches

Technique How the skill applies it
Curated, not crawled "Small but mighty — curated for signal, not volume." Every example is hand-vetted, so anatomy patterns aren't averaged across junk prompts.
Constraint-based prompts Each entry uses explicit negations ("no nudity," "no existing copyrighted characters") and bounded descriptors.
Local guides bundled with the skill The agent has on-disk reference markdown to consult before issuing a generation — closes the loop where the model would otherwise improvise parameters.
Workflow caution An on-skill warning instructs the agent to treat outputs as sketches, never as ground-truth anatomy for research figures.
Reproducibility Prompts are versioned alongside seed/parameter metadata so anatomy regressions are catchable in diffs.

Best for

Teams that want an installable, callable skill — not a copy-paste cookbook. Plays nicely with claude-code plugin marketplaces and Codex skill installers.

# Claude Code
/plugin marketplace add wuyoscar/gpt_image_2_skill
/plugin install gpt-image@wuyoscar-skills

3. stable-diffusion-negative-prompts — the anti-hallucination vocabulary

Location: skills/stable-diffusion-negative-prompts/ Upstream: https://github.com/mikhail-bot/stable-diffusion-negative-prompts License: see upstream LICENSE

What it gives you

A short, dense list of negative-prompt strings collected from Prodia, Reddit, ImgSli, and community contributors. Every string is engineered around anatomical failure modes. The repo's entire purpose is captured in this single canonical block:

((((ugly)))), (((duplicate))), ((morbid)), ((mutilated)), out of frame, extra fingers, mutated hands, ((poorly drawn hands)), ((poorly drawn face)), (((mutation))), (((deformed))), ((ugly)), blurry, ((bad anatomy)), (((bad proportions))), ((extra limbs)), cloned face, (((disfigured))), out of frame, ugly, extra limbs, (bad anatomy), gross proportions, (malformed limbs), ((missing arms)), ((missing legs)), (((extra arms))), (((extra legs))), mutated hands, (fused fingers), (too many fingers), (((long neck)))

The taxonomy of hallucinations it neutralises

Failure mode Tokens it forbids
Hands & fingers extra fingers, fused fingers, too many fingers, missing fingers, extra digit, fewer digits, broken finger, twisted fingers, disfigured hand, poorly drawn hands
Limbs extra limbs, missing arms, missing legs, extra arms, extra legs, malformed limbs, floating limbs, disconnected limbs, missing limb, split limbs, disembodied limb, linked limb
Body proportions bad anatomy, gross proportions, long neck, long body, bad proportions, disfigured butt, extra knee, extra elbow
Faces poorly drawn face, cloned face, 2 heads, 2 faces, cross-eye, squint, deformed face, irregular face, blurred faces
General morphology mutated, mutation, deformed, disfigured, mutilated, morbid, amputee, severed, dismembered
Quality / framing out of frame, cropped, low-res, blurry, jpeg artifacts, watermark, signature

These tokens generalise: they work for human anatomy, skeletons (the same "extra limbs / fused" failure modes apply), and animals (apply to legs, paws, ears, tails — the same vocabulary catches polydactyl pets and four-eared rabbits).

Best for

Dropping straight into the negative prompt field of any Stable Diffusion, SDXL, Flux, or ComfyUI workflow. Also a useful seed list when authoring "Avoid:" clauses for closed-source models that don't expose a dedicated negative-prompt parameter (GPT-Image-2, Nano Banana, Midjourney v6+ with --no).


How the three fit together

   ┌─────────────────────────────────────────────────────────┐
   │  USER INTENT: "Draw a skeleton holding a cat"           │
   └─────────────────────────────────────────────────────────┘
                 │
                 ▼
   ┌─────────────────────────────────────────────────────────┐
   │  2. GPT-Image2-Skill                                    │
   │     - Agent picks the closest gallery exemplar          │
   │     - Loads parameter cheatsheet                        │
   │     - Issues a structured prompt                        │
   └─────────────────────────────────────────────────────────┘
                 │
                 ▼
   ┌─────────────────────────────────────────────────────────┐
   │  1. awesome-gpt-image-2-API-and-Prompts                 │
   │     - Lifts the matching positive prompt + Avoid clause │
   │     - Anchors identity with a reference image           │
   └─────────────────────────────────────────────────────────┘
                 │
                 ▼
   ┌─────────────────────────────────────────────────────────┐
   │  3. stable-diffusion-negative-prompts                   │
   │     - Appends the anatomy negative vocabulary           │
   │     - (or: rephrased as "Avoid:" for GPT-Image-2)       │
   └─────────────────────────────────────────────────────────┘
                 │
                 ▼
                Image (audited against reference)

Selection methodology

GitHub repository search on 2026-05-27, sorted by stars, intersected with the following criteria:

  1. Explicit focus on prompts or agent skills (not model weights, not apps, not 3D viewers).
  2. Demonstrable coverage of human anatomy / skeletons / animal drawing, either via dedicated cases or via vocabulary that targets anatomical failure modes.
  3. Active maintenance in the last 12 months (pushed:>2025-05-27).
  4. Real signal — not Coursera-class fork chains.

Queries that produced the shortlist:

  • anatomy drawing AI prompt skill in:name,description,readme stars:>10
  • claude skill drawing anatomy svg in:name,description,readme
  • stable-diffusion-negative-prompts sort:stars
  • awesome claude skills sort:stars (for skill-format candidates)

Honourable mentions that lost on either stars or scope:

  • Sunwood-ai-labs/draw-io-skill — diagrams, not anatomy.
  • Agents365-ai/excalidraw-skill — hand-drawn style, no anatomy gallery.
  • bentossell/visualise — inline SVG, agent-focused, but no anatomy coverage.
  • minimaxir/stable-diffusion-negative-prompt — experimentation notebook rather than a reusable vocabulary.

Repo layout

exec_dashbd/
├── LICENSE
├── README.md                                ← you are here
└── skills/
    ├── awesome-gpt-image-2-API-and-Prompts/  (subtree @ EvoLinkAI/main)
    ├── GPT-Image2-Skill/                     (subtree @ wuyoscar/main)
    └── stable-diffusion-negative-prompts/    (subtree @ mikhail-bot/main)

Each subtree carries its own LICENSE and README.md; refer to those for upstream license terms and contribution guidelines.

Updating a subtree from upstream

# Pull latest from any one of the three
git subtree pull --prefix=skills/awesome-gpt-image-2-API-and-Prompts \
  https://github.com/EvoLinkAI/awesome-gpt-image-2-API-and-Prompts.git main --squash

git subtree pull --prefix=skills/GPT-Image2-Skill \
  https://github.com/wuyoscar/GPT-Image2-Skill.git main --squash

git subtree pull --prefix=skills/stable-diffusion-negative-prompts \
  https://github.com/mikhail-bot/stable-diffusion-negative-prompts.git main --squash

License

This curation/README is released under the repo's existing LICENSE. Each vendored subtree retains its own upstream license; do not re-license their contents.

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