create-explanatory-image
Generate explanatory diagrams and infographics that visually communicate concepts.
Skill by Ruby
Install
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
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
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:
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Signals
- Stars
- 0
- Forks
- 1
- Open issues
- 1
- 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
- Repository
- github.com/Abilityai/trinity-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Cite this page
create-explanatory-image skill. Agent Mart. https://agentmart.dev/skills/abilityai-create-explanatory-image (last updated 2026-10-24)