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Agent skill

Inno Figure Gen

by LigphiDonk in LigphiDonk/Oh-my--paper

Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image).

MITAuto-check passedMedia & Creative

Install Inno Figure Gen

skills CLI
$ npx skills add LigphiDonk/Oh-my--paper --skill inno-figure-gen -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LigphiDonk/Oh-my--paper inno-figure-gen --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LigphiDonk/Oh-my--paper.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/inno-figure-gen .claude/skills/inno-figure-gen && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
inno-figure-gen
GitHub stars
739
Token cost
~1.9k tokens
SKILL.md length
747 words
Files
2 (incl. scripts)
Skills in repo
27
Repo updated
First seen
Licence
MIT

At a glance

Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image).

  • Works in 2 steps: api-key argument (use if user provided… → GEMINI_API_KEY environment variable
  • Tasks that involve Image generation
  • SKILL.md covers Canonical Summary, Trigger Rules, Resource Use Rules and Execution Contract, plus 12 more sections
  • Runs Python scripts from its folder; calls uv; needs GEMINI_API_KEY

What it does

Inno Figure Gen is an agent skill from LigphiDonk/Oh-my--paper. Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image).

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/generate_image.py`).

It sits in Media & Creative, covering Image generation and Image editing. It works with Google Gemini. The repository describes itself as: A Claude Code plugin that turns your terminal into an autonomous research lab — literature survey, experiment execution, paper writing, all in one pipeline. The licence is MIT.

When your agent uses it

  • Tasks that involve Image generation
  • Tasks that involve Image editing

Example prompts

  • “/inno-figure-gen”

Requirements

  • Python 3
  • A credential in GEMINI_API_KEY

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

  1. api-key argument (use if user provided key in chat)
  2. GEMINI_API_KEY environment variable

What it can do on your machine

Read from SKILL.md and the folder at commit 6baece9. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GEMINI_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Inno Figure Gen loads about 1.9k tokens when it runs. Until then it costs about 20 tokens; SKILL.md has 747 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~20
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LigphiDonk/Oh-my--paper at commit 6baece9, republished under its MIT licence (© LigphiDonk). 747 words, ~1,907 tokens.

Download SKILL.mdSave it as .claude/skills/inno-figure-gen/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
inno-figure-gen
description
Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image).
id
inno-figure-gen
version
1.0.0
stages
publication
tools
read_file, search_project, write_file, run_terminal
summary
Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image). Use for image create/modify requests incl. edits. Supports text-to-image + image-to-image…
primaryIntent
writing
intents
writing
capabilities
visualization-reporting
domains
general
keywords
inno-figure-gen, paper writing, visualization-reporting, inno, figure, gen, generate, edit, images, nano, banana, pro

inno-figure-gen

Canonical Summary

Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image). Use for image create/modify requests incl. edits. Supports text-to-image + image-to-image; 1K/2K/4K; use --input-image.

Trigger Rules

Use this skill when the user request matches its research workflow scope. Prefer the bundled resources instead of recreating templates or reference material. Keep outputs traceable to project files, citations, scripts, or upstream evidence.

Resource Use Rules

  • Treat scripts/ as optional helpers. Run them only when their dependencies are available, keep outputs in the project workspace, and explain a manual fallback if execution is blocked.

Execution Contract

  • Resolve every relative path from this skill directory first.
  • Prefer inspection before mutation when invoking bundled scripts.
  • If a required runtime, CLI, credential, or API is unavailable, explain the blocker and continue with the best manual fallback instead of silently skipping the step.
  • Do not write generated artifacts back into the skill directory; save them inside the active project workspace.

Upstream Instructions

Nano Banana Pro Image Generation & Editing

Generate new images or edit existing ones using Google's Nano Banana Pro API (Gemini 3 Pro Image).

Usage

Run the script using absolute path (do NOT cd to skill directory first):

Generate new image:

bash
uv run ~/.codex/skills/inno-figure-gen/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--resolution 1K|2K|4K] [--api-key KEY]

Edit existing image:

bash
uv run ~/.codex/skills/inno-figure-gen/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--resolution 1K|2K|4K] [--api-key KEY]

Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.

Default Workflow (draft → iterate → final)

Goal: fast iteration without burning time on 4K until the prompt is correct.

  • Draft (1K): quick feedback loop
    • uv run ~/.codex/skills/inno-figure-gen/scripts/generate_image.py --prompt "<draft prompt>" --filename "yyyy-mm-dd-hh-mm-ss-draft.png" --resolution 1K
  • Iterate: adjust prompt in small diffs; keep filename new per run
    • If editing: keep the same --input-image for every iteration until you’re happy.
  • Final (4K): only when prompt is locked
    • uv run ~/.codex/skills/inno-figure-gen/scripts/generate_image.py --prompt "<final prompt>" --filename "yyyy-mm-dd-hh-mm-ss-final.png" --resolution 4K

Resolution Options

The Gemini 3 Pro Image API supports three resolutions (uppercase K required):

  • 1K (default) - ~1024px resolution
  • 2K - ~2048px resolution
  • 4K - ~4096px resolution

Map user requests to API parameters:

  • No mention of resolution → 1K
  • "low resolution", "1080", "1080p", "1K" → 1K
  • "2K", "2048", "normal", "medium resolution" → 2K
  • "high resolution", "high-res", "hi-res", "4K", "ultra" → 4K

API Key

The script checks for API key in this order:

  1. --api-key argument (use if user provided key in chat)
  2. GEMINI_API_KEY environment variable

If neither is available, the script exits with an error message.

Preflight + Common Failures (fast fixes)

  • Preflight:

    • command -v uv (must exist)
    • test -n \"$GEMINI_API_KEY\" (or pass --api-key)
    • If editing: test -f \"path/to/input.png\"

  • Common failures:

    • Error: No API key provided. → set GEMINI_API_KEY or pass --api-key
    • Error loading input image: → wrong path / unreadable file; verify --input-image points to a real image
    • “quota/permission/403” style API errors → wrong key, no access, or quota exceeded; try a different key/account
Show full SKILL.md (297 more words)Show less

Filename Generation

Generate filenames with the pattern: yyyy-mm-dd-hh-mm-ss-name.png

Format: {timestamp}-{descriptive-name}.png

  • Timestamp: Current date/time in format yyyy-mm-dd-hh-mm-ss (24-hour format)
  • Name: Descriptive lowercase text with hyphens
  • Keep the descriptive part concise (1-5 words typically)
  • Use context from user's prompt or conversation
  • If unclear, use random identifier (e.g., x9k2, a7b3)

Examples:

  • Prompt "A serene Japanese garden" → 2025-11-23-14-23-05-japanese-garden.png
  • Prompt "sunset over mountains" → 2025-11-23-15-30-12-sunset-mountains.png
  • Prompt "create an image of a robot" → 2025-11-23-16-45-33-robot.png
  • Unclear context → 2025-11-23-17-12-48-x9k2.png

Image Editing

When the user wants to modify an existing image:

  1. Check if they provide an image path or reference an image in the current directory
  2. Use --input-image parameter with the path to the image
  3. The prompt should contain editing instructions (e.g., "make the sky more dramatic", "remove the person", "change to cartoon style")
  4. Common editing tasks: add/remove elements, change style, adjust colors, blur background, etc.

Prompt Handling

For generation: Pass user's image description as-is to --prompt. Only rework if clearly insufficient.

For editing: Pass editing instructions in --prompt (e.g., "add a rainbow in the sky", "make it look like a watercolor painting")

Preserve user's creative intent in both cases.

Prompt Templates (high hit-rate)

Use templates when the user is vague or when edits must be precise.

  • Generation template:

    • “Create an image of: <subject>. Style: <style>. Composition: <camera/shot>. Lighting: <lighting>. Background: <background>. Color palette: <palette>. Avoid: <list>.”

  • Editing template (preserve everything else):

    • “Change ONLY: <single change>. Keep identical: subject, composition/crop, pose, lighting, color palette, background, text, and overall style. Do not add new objects. If text exists, keep it unchanged.”

Output

  • Saves PNG to current directory (or specified path if filename includes directory)
  • Script outputs the full path to the generated image
  • Do not read the image back - just inform the user of the saved path

Examples

Generate new image:

bash
uv run ~/.codex/skills/inno-figure-gen/scripts/generate_image.py --prompt "A serene Japanese garden with cherry blossoms" --filename "2025-11-23-14-23-05-japanese-garden.png" --resolution 4K

Edit existing image:

bash
uv run ~/.codex/skills/inno-figure-gen/scripts/generate_image.py --prompt "make the sky more dramatic with storm clouds" --filename "2025-11-23-14-25-30-dramatic-sky.png" --input-image "original-photo.jpg" --resolution 2K

© LigphiDonk, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in skills/inno-figure-gen of LigphiDonk/Oh-my--paper.

  • SKILL.md
  • scripts/generate_image.py

Open the folder on GitHubat commit 6baece9

Compare with similar skills

Inno Figure Gen next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Inno Figure Gen compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Inno Figure Gen this skillLigphiDonk/Oh-my--paper739—~1.9kAutomated safety check: PassMIT
AI Image Generation and Editingzhayujie/CowAgent47k—~1.3kAutomated safety check: PassMIT
BlockRun Image GenerationBlockRunAI/ClawRouter6.6k—~2.1kAutomated safety check: PassMIT
Antigravity Gemini ImageuluckyXH/OpenMOSS1.3k—~730Automated safety check: NotesMIT
FigureMuuuun/luxas1.2k—~1.2kAutomated safety check: PassMIT
Gemini Image Generatordair-ai/dair-academy-plugins6142 repos~3.5kAutomated safety check: NotesMIT

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Works with

Categories

Questions about Inno Figure Gen

What does Inno Figure Gen do?

Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image). Inno Figure Gen is an agent skill from LigphiDonk/Oh-my--paper. Generate/edit images with Nano Banana Pro (Gemini 3 Pro Image).

When should I use Inno Figure Gen?

Inno Figure Gen fits situations like: tasks that involve Image generation; tasks that involve Image editing.

How do I install Inno Figure Gen in Claude Code?

Run `npx skills add LigphiDonk/Oh-my--paper --skill inno-figure-gen -a claude-code`. Or copy the skill folder (skills/inno-figure-gen in LigphiDonk/Oh-my--paper) into .claude/skills/inno-figure-gen in your project. Claude Code loads it when a task matches its description.

How do I install Inno Figure Gen in Codex?

Run `npx skills add LigphiDonk/Oh-my--paper --skill inno-figure-gen -a codex`. Or copy the skill folder (skills/inno-figure-gen in LigphiDonk/Oh-my--paper) into .agents/skills/inno-figure-gen in your project. Codex loads it when a task matches its description.

Can I use Inno Figure Gen in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LigphiDonk/Oh-my--paper --skill inno-figure-gen -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/inno-figure-gen, .gemini/skills/inno-figure-gen, .github/skills/inno-figure-gen and .opencode/skills/inno-figure-gen in your project.

What does Inno Figure Gen need to run?

Going by SKILL.md and its folder, Inno Figure Gen needs Python for the scripts in its folder, the command-line tools its instructions call (uv) and credentials named GEMINI_API_KEY. Our summary lists: Python 3; A credential in GEMINI_API_KEY.

Does Inno Figure Gen access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Inno Figure Gen safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Inno Figure Gen use?

Inno Figure Gen is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Inno Figure Gen use?

About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Inno Figure Gen?

Skills that share tags, products or a category with Inno Figure Gen: AI Image Generation and Editing (zhayujie/CowAgent, 47k stars), BlockRun Image Generation (BlockRunAI/ClawRouter, 6.6k stars), Antigravity Gemini Image (uluckyXH/OpenMOSS, 1.3k stars) and Figure (Muuuun/luxas, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Inno Figure Gen?

LigphiDonk (a GitHub user) maintains it in LigphiDonk/Oh-my--paper, which has 739 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on April 15, 2026.

Source: LigphiDonk/Oh-my--paper on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.