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jpcaparas/skills108 installs

nanobanana-infographic

Create infographic prompts and render workflows with Nano Banana 2, with adaptable low-noise presets for posts, decks, reports, and explainers. Trigger on infographic, Nano Banana 2, Gemini image, executive visual, blog diagram, or presentation visual. Do NOT use for logos, memes, or raw dashboards.

How do I install this agent skill?

npx skills add https://github.com/jpcaparas/skills --skill nanobanana-infographic
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    The skill is a professional developer tool for generating and verifying Nano Banana 2 (Gemini 3.1 Flash Image) infographic prompt packs. It implements a structured workflow involving local scripts to build prompts, batch-render them concurrently, and probe official Gemini API endpoints. The skill adheres to security best practices by utilizing environment variables for credentials and targeting trusted Google API services for all network operations.

  • Socketpass

    No alerts

  • Snykpass

    Risk: LOW · No issues

  • ZeroLeakspass

    Score: 93/100 · 2 sections analyzed

What does this agent skill do?

Nano Banana 2 Infographic

Create legible, fact-faithful infographics that fit the user's brief. Low-noise editorial layouts are useful presets, not the only valid style.

This skill uses Nano Banana 2 only. For API calls, use its callable model ID rather than assuming the public marketing name is the exact endpoint name. If the documented ID is uncertain, unavailable, or conflicts with observed behavior, verify current official model documentation and, when authorized, model availability. Do not silently substitute another model.

Decision Tree

What do you need to do?

  • The brief is incomplete or fuzzy Infer sensible essentials from the context. Ask only when a missing fact or unresolved choice would materially change the result; do not invent factual claims.

  • The user wants an infographic now Create the requested number in the requested format and style; an unspecified singular request means one image, not a four-render pack. Use references/patterns.md for composition examples when helpful.

  • The user wants live Gemini renders or proof that the prompt works Read references/configuration.md, confirm the authorized scope and spend, then use the single-prompt or batch route that fits.

  • The user wants exact API syntax, model IDs, or request fields Read references/api.md.

  • The result looks noisy, text-heavy, or poster-like Read references/gotchas.md if needed, diagnose the mismatch with the brief, and revise. A bold poster-like style is not itself a defect.

Default Operating Mode

  • Let the requested count, channel, ratio, style, palette, and content control the result. Otherwise choose a coherent composition suited to the audience; explain material assumptions briefly.
  • Author a custom prompt directly when the presets do not fit. Dark canvases, bold palettes, gradients, longer text, and other layouts are valid when legible and appropriate.
  • Use separate requests for distinct images rather than trusting one request to return an exact image count. Check the actual outputs.
  • Render only the authorized images and passes. A prompt-only request needs no API call; a single-image request does not authorize four paid alternatives or open-ended retries.
  • Preserve exact facts, units, qualifiers, labels, and required attribution. Decide visible copy before rendering and inspect it afterward; never truncate meaning merely to satisfy a word-count preset.
  • Keep credentials secret and send only content authorized for the external service. Saved prompts and responses can contain sensitive material; do not publish them by default.

Intake Questions

Use these only for material gaps that cannot be resolved from the brief:

MissingAsk
Topic or claim"What is the infographic about, in one sentence?"
Audience or channel"Where will this live: blog post, deck, report, keynote, or something else?"
Facts or sections"Which numbers, claims, or sections must appear?"
Style boundaries"Any brand colours, must-avoid looks, or reference tone?"

If the essentials are supplied or reasonably inferable, proceed without a questionnaire. Missing optional style preferences are not a blocker.

Quick Reference

NeedDoOutput
Custom imageWrite a prompt directly; use scripts/probe_gemini_image_api.py only for an authorized renderthe requested composition without preset constraints
Low-noise prompt packRun scripts/build_variant_pack.py with a brief JSON1-4 preset prompts; defaults to four, with a markdown review sheet
Approved parallel renderRun scripts/render_variant_pack.py on a reviewed packall included variants rendered concurrently plus a batch manifest
Optional composition examplesTry Executive Snapshot, Editorial Column, Decision Board, or Insight Ribbonstarting points, not an exhaustive design menu
Noise reductionRemove extra panels, colors, and prose before re-renderingcleaner second pass

Optional Low-Noise Presets

For restrained slide or blog visuals, try 16:9, a white or near-white base, 2-3 accents, a title of roughly five words, and short labels with explanation outside the image. These are starting choices, not universal limits; retain longer required copy, source notes, or paragraphs when the format needs them. The generator implements a stricter preset, including title truncation: see references/configuration.md before using it for exact wording or custom styles.

VariantBest ForDirection
Executive SnapshotC-suite slides, board pre-reads, strategic summariesone dominant claim or number with 3-4 disciplined support blocks
Editorial ColumnBlog posts, reports, explainerstall stacked panels with generous whitespace and thin dividers
Decision Boardtrade-offs, frameworks, comparisonsmodular grid or side-by-side layout with equal visual weight
Insight Ribbonkeynote hero slides, opener visuals, and wide summariesone horizontal narrative band with evenly spaced support modules

Use references/patterns.md for adaptable prompt shapes and targeted iteration.

Rendering Rules

  • State the chosen ratio in both the prompt and API configuration; use a supported format rather than silently overriding the user's target.
  • Organize related ideas with clear hierarchy. Combined process, comparison, illustration, or glossary elements can work if their relationships remain understandable.
  • Verify text and visual encodings at the intended display size, including contrast and meaning beyond color alone. Supply alt text or a text equivalent when delivering an image for accessible publication.
  • Fix factual errors, missing required content, and illegibility before delivery. Plan further paid attempts within the user's scope rather than rerendering automatically until a subjective style target is met.

Gotchas

  1. Asking for a "detailed infographic" usually increases clutter rather than clarity. Ask for hierarchy, whitespace, and restraint instead.
  2. Google documents that the model might not create the exact number of images requested. Use one deliberate request per intended image, then inspect the returned count.
  3. Google also documents that text generation works best when the text is decided first and then rendered into the image. Do not improvise long copy inside the image prompt.
  4. If the image misses the intended tone or scan path, adjust hierarchy, grouping, or emphasis without discarding a requested bold style.
  5. When the user needs dense quantitative fidelity, hand-built charts or vector layouts may be a better fit than Gemini image generation.

Keeping Guidance Useful

Rely on stable principles: factual fidelity, hierarchy, contrast, legibility, and fit to the publishing context. When guidance is insufficient or conflicts with observed behavior, consult current official Gemini/tool documentation or trusted subject sources for the disputed fact; do not browse on every prompt-writing task. Propose a sourced correction to the canonical skill with an example or check, rather than silently changing installed copies. Historical model probes are evidence from that date, not a guarantee of current availability.

Reading Guide

TaskRead
Model IDs, request fields, aspect ratios, response shapereferences/api.md
Variant design, question flow, prompt formula, iteration ladderreferences/patterns.md
Environment setup, scripts, and live verification commandsreferences/configuration.md
Noise, text, language, and retry pitfallsreferences/gotchas.md

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

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