ClaudeCodeMod

All shelves / Skills

nano-banana-2

runcomfy-com/skills · 273.7k installs · 15 stars

Skill Generate images with Google Nano Banana 2 (Gemini-family flash-tier text-to-image) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Nano Banana 2's strengths (rapid iteration, in-image typography rendering, predictable framing, optional web-grounded context), the resolution-tier pricing, the safety-tolerance dial, and when to route to Nano Banana Pro / GPT Image 2 / Flux 2 / Seedream instead. Calls `runcomfy run google/nano-banana-2/text-to-image` through the local RunComfy CLI. Triggers on "nano banana", "nano-banana-2", "nano banana 2", "google image gen", "gemini image", or any explicit ask to generate with this model.

Install

In your shell
npx -y skills add runcomfy-com/skills --skill nano-banana-2 --agent claude-code

Run in a terminal. Claude loads the skill when a task calls for it. Check the repo's README before you run it.

Open the repo

Files

SKILL.md

Nano Banana 2 — Pro Pack on RunComfy

runcomfy.com · Model page · GitHub

Google Nano Banana 2 — the flash-tier text-to-image model in the Gemini family — hosted on the RunComfy Model API. Optimized for ideation, social-thumbnail batches, and rapid drafts with strong in-image typography.

npx skills add agentspace-so/runcomfy-skills --skill nano-banana-2 -g

When to pick this model (vs siblings)

Nano Banana 2 is the flash-tier of the Google image-gen line. Pick it when iteration speed and predictable framing matter more than maximum detail.

You want Use
Rapid drafts, social thumbnails, batch variants Nano Banana 2
In-image typography with predictable rendering Nano Banana 2
Web-grounded image (current events / real entities) Nano Banana 2 + enable_web_search
Image edit (preserve subject, swap background) Nano Banana Edit (sibling skill)
Heavy stylization, painterly look Flux 2
Maximum prompt adherence + multilingual text GPT Image 2
2K–4K hero shots, max realism Seedream 5
Hyperrealistic portrait Nano Banana Pro

If the user said "Nano Banana" / "nano-banana-2" / "Gemini image" explicitly, route here regardless. If they said "Nano Banana" without specifying 2 vs Pro, default to Pro for portraits and 2 for everything else.

Prerequisites

  1. RunComfy CLI — npm i -g @runcomfy/cli
  2. RunComfy account — runcomfy login opens a browser device-code flow.
  3. CI / containers — set RUNCOMFY_TOKEN=<token> instead of runcomfy login.

Endpoints + input schema

google/nano-banana-2/text-to-image

Field Type Required Default Notes
prompt string yes — Subject-first description.
num_images int no 1 1–4. Use 4 for ideation rounds.
seed int no 0 Reuse for reproducibility.
aspect_ratio enum no auto auto, 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16.
resolution enum no 1K 0.5K (drafts), 1K (default), 2K (final), 4K (max).
output_format enum no png png, jpeg, webp.
safety_tolerance int no 4 1 (strict) – 6 (permissive).
limit_generations bool no true Limit each prompt round to one generation.
enable_web_search bool no false Adds web grounding (extra cost + latency).

For image edit (preserve subject + apply changes), see the sibling nano-banana-edit skill.

How to invoke

Default draft (1K, square, png):

runcomfy run google/nano-banana-2/text-to-image \
  --input '{"prompt": "<user prompt>"}' \
  --output-dir <absolute/path>

Vertical 4-up batch for ideation:

runcomfy run google/nano-banana-2/text-to-image \
  --input '{
    "prompt": "<user prompt>",
    "num_images": 4,
    "aspect_ratio": "9:16",
    "resolution": "0.5K"
  }' \
  --output-dir <absolute/path>

Final at 2K with seed lock:

runcomfy run google/nano-banana-2/text-to-image \
  --input '{
    "prompt": "<user prompt>",
    "resolution": "2K",
    "aspect_ratio": "16:9",
    "seed": 42
  }' \
  --output-dir <absolute/path>

Web-grounded (current event / real entity):

runcomfy run google/nano-banana-2/text-to-image \
  --input '{
    "prompt": "<prompt referencing a real-world event from this week>",
    "enable_web_search": true
  }' \
  --output-dir <absolute/path>

Prompting — what actually works

Subject-first declarative grammar. "A cinematic close-up portrait of an American woman standing under neon lights in rainy Tokyo, shallow depth of field, reflective wet streets, ultra-detailed, realistic skin texture" — primary subject, then action, environment, style, camera. Front-load subject; trail with directives.

Exact text quoting for in-image typography. "The label reads 'AURA' in clean bold sans-serif, centered, white on black" — quote the literal characters. Specify placement and font style. Don't say "with the brand name on it" and hope.

Consistent seeds for refinement. Lock seed when iterating a single prompt across small variants — keeps composition stable.

Web-grounding, sparingly. Turn on enable_web_search only when the prompt names current events / real entities. Adds latency + cost; off by default.

Don't conflict styles. "minimalist + ornate + retro + cyberpunk" cancels. Pick 1–2 anchors.

Anti-patterns:

  • Trying to verbally describe a stable subject identity — use the edit endpoint with image refs instead.
  • Asking for resolutions outside the 4 tiers → 422.
  • Aspect ratios outside the 11 supported values → 422.
  • Non-quoted in-image text → unpredictable rendering.

Where it shines

Use case Why Nano Banana 2
Marketing draft thumbnails (batch of 4) Fast iteration at 0.5K, then promote winner to 2K
Social-platform-native Wide aspect ratio support including 9:16, 4:5, 21:9
In-image typography for posters / cards Predictable text rendering when characters are quoted
Web-grounded current-event imagery enable_web_search integrates fresh info
Reproducible variant testing Strong seed + consistent framing

Sample prompts (verified to produce strong results)

Cinematic portrait (page example):

A cinematic close-up portrait of an American woman standing under neon
lights in rainy Tokyo, shallow depth of field, reflective wet streets,
ultra-detailed, realistic skin texture

Brand-asset card with quoted text:

A minimalist 16:9 product card: a matte black ceramic mug centered on a
soft warm-grey paper background, rim highlight from upper-left, the
headline "Brewed Quietly" in clean bold sans-serif top-right, balanced
negative space below, e-commerce ready, clean studio lighting

Vertical platform-native:

A 9:16 vertical hero for a wellness brand: a single ceramic teacup on a
linen runner, soft morning side-light, the words "Slow Down" in
hand-drawn serif large at the top, gentle steam rising, neutral color
palette, uncluttered

Limitations

  • Still images only. No video on this endpoint.
  • Max 4 outputs per request.
  • Web search adds latency + cost — only enable on demand.
  • 2K / 4K cost more — default to 1K unless user asked for higher.
  • For image edit, use the /edit endpoint — not this one.

Exit codes

code meaning
0 success
64 bad CLI args
65 bad input JSON / schema mismatch
69 upstream 5xx
75 retryable: timeout / 429
77 not signed in or token rejected

Full reference: docs.runcomfy.com/cli/troubleshooting.

How it works

The skill invokes runcomfy run google/nano-banana-2/text-to-image with a JSON body matching the schema. The CLI POSTs to https://model-api.runcomfy.net/v1/models/google/nano-banana-2/text-to-image, polls the request, fetches the result, and downloads any .runcomfy.net/.runcomfy.com URL into --output-dir. Ctrl-C cancels the remote request before exit.

Security & Privacy

  • Token storage: runcomfy login writes the API token to ~/.config/runcomfy/token.json with mode 0600 (owner-only read/write). Set RUNCOMFY_TOKEN env var to bypass the file entirely in CI / containers.
  • Input boundary: the user prompt is passed as a JSON string to the CLI via --input. The CLI does NOT shell-expand the prompt; it transmits the JSON body directly to the Model API over HTTPS. No shell injection surface from prompt content.
  • Third-party content: image / mask / video URLs you pass are fetched by the RunComfy model server, not by the CLI on your machine. Treat external URLs as untrusted; image-based prompt injection is a known risk for any image-edit / video-edit model.
  • Outbound endpoints: only model-api.runcomfy.net (request submission) and *.runcomfy.net / *.runcomfy.com (download whitelist for generated outputs). No telemetry, no callbacks.
  • Generated-file size cap: the CLI aborts any single download > 2 GiB to prevent disk-fill from a malicious or runaway model output.

Facts

Kind
Skill
Repo
runcomfy-com/skills
Group
Uncategorized
Installs
273.7k
Stars
15

More on this shelf

  1. 1find-skillsvercel-labs/skillsHelps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.3M
  2. 2ai-video-generationinference-sh/skillsGenerate AI videos with Google Veo, Seedance 2.0, HappyHorse, Wan, Grok and 40+ models via inference.sh CLI. Models: Veo 3.1, Seedance 2.0, HappyHorse 1.0, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Capabilities: text-to-video, image-to-video, reference-to-video, video editing, lipsync, avatar animation, video upscaling, foley sound. Use for: social media videos, marketing content, explainer videos, product demos, AI avatars. Triggers: video generation, ai video, text to video, image to video, veo, animate image, video from image, ai animation, video generator, generate video, t2v, i2v, ai video maker, create video with ai, runway alternative, pika alternative, sora alternative, kling alternative, seedance, happyhorse1.7M
  3. 3ai-image-generationinference-sh/skillsGenerate AI images with GPT-Image-2.5, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2.5 Flare, GPT-Image-2.5 Sunburst, GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpainting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, ai image, text to image, stable diffusion, generate image, ai art, midjourney alternative, dall-e alternative, text2img, t2i, image generator, ai picture, create image with ai, generative ai, ai illustration, grok image, gemini image, gpt image, openai image, chatgpt image1.7M
  4. 4ai-avatar-videoinference-sh/skillsCreate AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Audio: Inworld TTS-2 (100+ languages, emotion steering for characters), ElevenLabs, Kokoro. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters, UGC content. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos, UGC ads, gaming avatars, NPC dialogue. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human, ugc, ugc video, ugc ad, avatar ugc1.7M
  5. 5twitter-automationinference-sh/skillsAutomate Twitter/X with posting, engagement, and user management via inference.sh CLI. Apps: x/post-create (text and media), x/post-like, x/post-retweet, x/dm-send, x/user-follow. Capabilities: post tweets, schedule content, like posts, retweet, send DMs, follow users, get profiles. Use for: social media automation, content scheduling, engagement bots, audience growth, X API. Triggers: twitter api, x api, tweet automation, post to twitter, twitter bot, social media automation, x automation, tweet scheduler, twitter integration, post tweet, twitter post, x post, send tweet1.7M
  6. 6remotion-renderinference-sh/skillsRender videos from React/Remotion component code via inference.sh. Pass TSX code, get MP4. Supports all Remotion APIs: useCurrentFrame, useVideoConfig, spring, interpolate, AbsoluteFill, Sequence. Configurable resolution, FPS, duration, codec. Use for: programmatic video generation, animated graphics, motion design, data-driven videos, React animations to video. Triggers: remotion, render video from code, tsx to video, react video, programmatic video, remotion render, code to video, animated video, motion graphics code, react animation video1.6M