Transparent Icons

Transparent Icons

Generate flat scientific icons (Nature/Science journal style) with transparent backgrounds. Used as panel elements by the [[scientific-figure]] composer or as standalone graphics for posters, presentations, and grants.

Backends

Two generation backends, auto-selected:

1. Codex CLI image_gen tool (preferred). Uses the local Codex authentication (~/.codex/auth.json). No OPENAI_API_KEY required. Internally uses gpt-image-2 (April 2026). Default when codex is on $PATH and authenticated.
2. OpenAI Images API (fallback). Calls client.images.generate(model="gpt-image-2", ...) directly. Requires OPENAI_API_KEY in environment or .env.

Why two backends: many researchers have a ChatGPT subscription and codex login but no separate API key. Auto-selection routes through Codex first to keep the no-API-key path working; explicit --backend codex or --backend api overrides.

Transparency

gpt-image-2 (April 2026) does not accept background="transparent" — both backends always generate opaque PNGs. Transparency is applied as a post-process. Two methods:

• threshold (default) — drop near-white pixels via Pillow. Fast, no extra deps. Works well for flat 2-color icons on a clean white background. Can leave fringes on anti-aliased edges and may erase highlights where the foreground itself is near-white.
• birefnet (opt-in) — rembg + BiRefNet ONNX model with alpha matting. Cleaner edges, handles complex foregrounds. One-time ~400 MB model download on first run; requires extra deps (rembg, onnxruntime).

Pick threshold for the canonical flat-icon use case. Pick birefnet when the icon contains light-colored content (white parts of a brain MRI, light reflections on glass) that the threshold method would erase, or when the icon will be composited at large sizes where fringes are visible.

Usage

Free-form prompt:

uv run --with openai --with python-dotenv --with pillow python scripts/generate_icon.py \
    "a human brain with EEG electrodes" -o brain_eeg.png --transparent

From the icon bible (curated templates with palettes, descriptions, and prompt hints):

uv run --with openai --with python-dotenv --with pillow python scripts/generate_icon.py \
    --template brain-eeg -o brain_eeg.png --transparent

With BiRefNet transparency (higher edge quality, extra deps):

uv run --with openai --with python-dotenv --with pillow --with rembg --with onnxruntime \
    python scripts/generate_icon.py --template neuron -o neuron.png \
    --transparent --transparency-method birefnet

List templates:

uv run --with python-dotenv python scripts/generate_icon.py --list-templates

Force a specific backend:

... --backend codex   # or --backend api

Theme bible: keep an icon set consistent

When generating multiple icons that need to look like they belong together (same line weight, same color palette, same perspective), use a theme.json file. The schema is in references/theme.schema.json and is shared with the [[ai-full-figure]] skill. At a minimum:

{
  "theme_id": "neuro-flat-v1",
  "palette": {"primary": "#1F3A5F", "accent": "#E07A5F", "neutral": "#F4F1DE", "bg": "transparent"},
  "stroke": {"weight_px": 4, "linejoin": "round"},
  "style_tokens": ["flat 2D", "single continuous line", "no shading", "centered"],
  "negative_tokens": ["text", "labels", "watermark", "gradient", "3D", "shadow"],
  "composition": {"aspect": "1:1", "padding_pct": 12, "perspective": "orthographic"}
}

examples/icon_set.py demonstrates loading a theme (including stroke weight and line-join hints) and generating an icon set with consistent prompts.

When to use this skill vs the icon bible

• Bible templates (--template ) are curated for common research subjects (brain, neuron, EEG cap, DNA, microscope, etc.) and produce predictable output. Use them first.
• Free-form prompts are right when the subject is not in the bible or needs a specific composition not captured by a template.
• --category generates every template in a category at once; useful for stocking a project's icon directory.

See references/icon-bible.md for the template schema and references/prompt-patterns.md for what works and what to avoid in prompts.

Quality assurance

The [[figure-qa]] agent proactively runs on generated icons to check for transparency correctness (alpha-channel + corner sampling), palette compliance (with near-gray exemption for chrome), DPI vs the journal target, and dominant colors. Pass --expect-transparent so the raster branch flags any opaque output as a regression.

Additional resources

• references/icon-bible.md — icon template schema and category catalog
• references/prompt-patterns.md — model-specific prompt patterns and failure modes
• references/theme.schema.json — JSON schema for the theme bible (shared with ai-full-figure)
• scripts/generate_icon.py — CLI entry point with auto backend selection
• scripts/icon-templates.json — bible templates loaded by --template / --category
• examples/icon_set.py — generate a 3-icon set with a shared theme (use --smoke for a single-icon verification run)

Source & license

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

• Author: neuromechanist
• Source: neuromechanist/research-skills
• License: BSD-3-Clause

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