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create-explanatory-image

Generate explanatory diagrams and infographics that visually communicate concepts.

Skill by Ruby

IndexedApache-2.0
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/abilityai-create-explanatory-image

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About

Generate explanatory diagrams and infographics that visually communicate concepts. Iterates autonomously until images are logically correct, text is clean, and the concept explanation is clear. Uses Nano Banana 2 (Gemini 3.1 Flash Image).

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Secrets
None asked for
Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/create-explanatory-image

Tools it pre-approves 5

From allowed-tools in SKILL.md: the agent may use these without asking you each time.

  • Bash,
  • Read,
  • Write,
  • Glob,
  • AskUserQuestion

What's inside

Skill name
create-explanatory-image
Description
Generate explanatory diagrams and infographics that visually communicate concepts. Iterates autonomously until images are logically correct, text is clean, and the concept explanation is clear. Uses Nano Banana 2 (Gemini 3.1 Flash Image).
License
Apache-2.0
Allowed tools
Bash,, Read,, Write,, Glob,, AskUserQuestion
Metadata
author: Ruby · created: 2026-03-03 · version: 1.1
Instructions
352 lines in SKILL.md · view on GitHub

Before installing

  • Pre-approves some shell commands

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Create Explanatory Image

## Purpose

Generate explanatory diagrams and infographics that clearly communicate a concept, iterating autonomously until the images are logically correct, text is accurate, and the visual explanation lands.

## Core Principles

Adapted from `/animated-explainer` - what makes an image *explain* rather than decorate.
Apply them at decomposition time (Steps 2-3); the self-critique loop (Step 5) checks them.

1. **The facts are the boss - interrogate before you design.** Decide what's TRUE before
   deciding what's compelling. If the image explains a real system, read its source of
   truth (specs, architecture docs, the actual data) - not marketing copy or published
   summaries. A concept the facts don't support dies at this step; that is the step
   working, not failing. Never soften an unsupported claim into a diagram.

2. **One concrete worked example beats any amount of abstraction.** A diagram that traces
   one real item end to end (this request, this invoice, this forecast) explains more
   than an abstract schema. Prefer a failure case the mechanism catches - it shows the
   machine doing its job and cannot be read as cherry-picking.

3. **Explainer, not advertisement.** Assume the viewer knows nothing. Open on the problem
   the mechanism solves - the title states what's broken or the single insight, not the
   product name. If the image only makes sense to someone who already understands the
   system, it has failed.

4. **Separate the mechanism from the numbers.** Carry the mechanism with symbolic marks;
   put real figures in ONE place (a footer stat, a single callout) or nowhere. If a mark
   is not 1:1 with a thing, say so on the image (`1 dot = ~30 runs`). Never silently mix
   scales. This also serves the 10-label limit.

5. **Lock the layout - nothing crosses anything.** One spine (a left-to-right flow or a
   single loop), elements sitting ON it. Crossing arrows read as *complexity*, not as a
   system. Prompt for it explicitly and reject renders where connections cross or wander.

6. **Nothing floats - every element visibly comes from somewhere.** The static cousin of
   "nothing teleports": causality is carried by explicit arrows and numbered steps
   (input -> transform -> output). An element with no incoming or outgoing connection is
   decoration - cut it or wire it in.

7. **Show the part that doesn't work.** If part of the system is unproven, planned, or
   broken, draw it dashed/hollow/greyed and label it. A diagram where everything works is
   the least trustworthy thing you can draw - the unfinished part is the credibility.

8. **Labels first.** Write every text string before generating anything (Step 2 does
   this) - if the labels alone, read in order, tell the story, the image will work. If
   they don't, no amount of visual polish will save it.

## State Dependencies

| Source | Location | Read | Write | Description |
|--------|----------|------|-------|-------------|
| Best practices | `.claude/skills/nano-banana-image-generator/best_practices.md` | yes | | Prompt engineering constraints and style guide |
| Generate script | `.claude/skills/nano-banana-image-generator/scripts/generate_image.py` | yes | | Image generation API |
| Output folder | User-specified or auto-created | | yes | Final and intermediate images |

## Prerequisites

- `GOOGLE_API_KEY` or `GEMINI_API_KEY` set in `.env`
- Nano Banana image generator scripts available at `.claude/skills/nano-banana-image-generator/scripts/`

## Inputs

- **Concept description**: What the diagram should explain (from user message or arguments)
- **Output folder** (optional): Where to save images. Default: auto-created folder named after the concept in current directory
- **Style** (optional): `dark` (black bg, brand style) or `warm` (charcoal bg, illustrated). Default: `warm`
- **Aspect ratio** (optional): `16:9`, `1:1`, `9:16`. Default: `16:9`
- **Variant count** (optional): How many initial variants. Default: 3

---

## Process

### Step 1: Read Current State

1. Read `.claude/skills/nano-banana-image-generator/best_practices.md`
   - Note complexity limits: **10 boxes max, 10 text labels max, 3 hierarchy levels max**
   - Note known model limitations (misspellings on 4+ syllable words, font inconsistency)

2. Confirm output folder:
   - If user specified a folder, use it
   - Otherwise, create: `[concept_slug]_diagrams/` in current directory
   - `mkdir -p [folder]`

### Step 2: Decompose the Concept

Analyze the user's concept description and break it down:

1. **Truth gate** (Principle 1): If the image describes a real system or carries real
   numbers, verify every claim against the source of truth (specs, docs, actual data) -
   never from memory or marketing copy. Cut anything unsupported and tell the user what
   was cut and why.
2. **Core message**: What single insight should the viewer walk away with? State it as
   the problem or insight, not the product name (Principle 3).
3. **Worked example** (Principle 2): Can the concept be shown as one concrete item traced
   end to end instead of an abstract schema? Prefer it; prefer a failure case the
   mechanism catches.
4. **Visual elements**: List all shapes, icons, nodes, connections needed. Every element
   must be wired into the flow (Principle 6) - an element with no incoming or outgoing
   connection gets cut or connected.
5. **Text labels**: List every text string that will appear in the image - then read them
   in order. If the labels alone tell the story, the image will work; if they don't, fix
   the story before generating anything (Principle 8).
6. **Honest state** (Principle 7): Which parts are live vs planned/unproven/broken? Mark
   the latter to render dashed, hollow, or greyed with a label.
7. **Layout type**: Identify the best diagram type:
   - Framework (central concept + surrounding elements)
   - Before/after comparison
   - Flow/process (horizontal or vertical)
   - Circular loop/cycle
   - Visual metaphor
   - Timeline/evolution
   - Cross-section/exploded view

### Step 3: Simplify for Constraints

**This step is critical.** The concept decomposition will almost always exceed Nano Banana's limits. Simplify ruthlessly:

From Abilityai/trinity-skills, Apache-2.0.

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Last commit (this folder)
Aug 4, 2026 (2 months ago)
Last release
Oct 21, 2026 (6 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
1.1
License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Cite this page

create-explanatory-image skill. Agent Mart. https://agentmart.dev/skills/abilityai-create-explanatory-image (last updated 2026-10-24)