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Nano banana

Skill tuoxie2046/claude-code-research-skills/skills/nano-banana

Generate images from the terminal with Google's nano-banana (Gemini image model) via the Antigravity CLI (`agy`), billed to the signed-in Google account. Use whenever the user asks to create / draw / generate an image, picture, icon, logo, illustration, poster, infographic, or diagram specifically with nano-banana / Gemini / Antigravity — or wants rich, text-heavy infographics. For the OpenAI gpt-image-2 path use the separate `gpt-image` skill instead.From its SKILL.md

Install
npx -y skills add tuoxie2046/claude-code-research-skills --skill nano-banana

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SKILL.md

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nano-banana — image generation via Antigravity (agy)

Wraps the agy (Google Antigravity) agent so Claude Code can generate images with nano-banana. Unlike a plain CLI, image generation here is an agent tool (generate_image) invoked through natural language — the wrapper builds a strict instruction, runs agy -p, then verifies the output file actually landed (with recovery from agy's brain/ working dir). Auth is the Google account signed into agy.

All commands go through the helper:

~/.claude/skills/nano-banana/scripts/nano-banana.sh <check|generate|batch> [args]

Workflow

  1. Preflight once per session: nano-banana.sh check. If it reports no creds / auth, the user must run agy once interactively to log in (browser OAuth) — you cannot do this for them. Token expiry surfaces at generate time as an auth error.
  2. Generate with an explicit --output PNG path. The helper prints IMAGE\t<path>\t<WxH> on success.
  3. Always Read the produced PNG to view it and verify, then report the path.
  4. Iterate by re-running with a refined prompt.

Commands

Generate (text → PNG):

~/.claude/skills/nano-banana/scripts/nano-banana.sh generate \
  --prompt "PROMPT TEXT" --output ./out.png

Batch (many prompts → many images; one per prompt, continue-on-error, manifest):

# from a file (one prompt per line; blank lines and # comments skipped)
~/.claude/skills/nano-banana/scripts/nano-banana.sh batch \
  --prompts-file ./prompts.txt --outdir ./renders
# inline / stdin
~/.claude/skills/nano-banana/scripts/nano-banana.sh batch --prompt "a" --prompt "b" --outdir ./out
printf 'one\ntwo\n' | ~/.claude/skills/nano-banana/scripts/nano-banana.sh batch --prompts-file -

Name an output by prefixing a line with stem<TAB>prompt (else 001.png, …). Default --outdir is ./nb-batch-<timestamp>/; read <outdir>/manifest.tsv for the stem→status→path→prompt map. Per-image failures are recorded and skipped, but an auth failure aborts the whole batch (no point retrying every prompt against dead auth) — re-login with agy and re-run.

How it works / behaviors

  • Underlying tool is generate_image (nano-banana is the model). There is no agy image subcommand — the agent calls the tool from the prompt.
  • The agent generates a JPEG into ~/.gemini/antigravity-cli/brain/<conv-id>/, then converts to PNG at your --output. The wrapper forces an absolute path and, if the agent doesn't save there, recovers the newest brain image and converts it via sips.
  • Output paths are absolutized (agy resets cwd). Parent dirs are created.
  • One retry on a no-file result; auth/eligibility errors fail fast with guidance.
  • Non-destructive: success requires the output file to actually change this run (checked via its inode:mtime:size), so a pre-existing/stale file is never reported as a fresh result and is not deleted if generation fails.

⚠️ Safety

This path drives an autonomous agent (agy -p … --dangerously-skip-permissions): tool calls and file writes are auto-approved. A prompt is therefore not just image text — a malicious or careless prompt could instruct the agent to run other tools or touch other files. Only pass trusted prompt text (and trusted --prompts-file contents). For the non-agent, capability-scoped path, prefer the gpt-image skill.

Strengths & limitations (vs gpt-image-2)

  • Strengths: excellent in-image text rendering; tends to produce rich, fully fleshed-out infographics (adds detail, gradients, sub-labels). Great for posters and content-heavy diagrams; strong at consistent image editing (via prompt + a file path).
  • Limitations:
    • No precise size control through the agent — it returns its own dimensions (often ~16:9). If you need an exact size, post-process with sips -z H W.
    • Slower than gpt-image-2 (it's an agent turn: tool call + format convert).
    • Tends to elaborate — if you want strictly minimal output, say "minimal, no extra text, exactly three boxes" etc.
    • Needs a live agy login; tokens expire and require interactive re-auth.

Troubleshooting

  • agy ... not found → install Antigravity (https://antigravity.google) or ensure ~/.local/bin is on PATH.
  • auth / IneligibleTier / "Authentication required" → run agy once interactively to log in; the standalone gemini CLI is not usable on free-tier accounts.
  • No file produced → check stderr for the agy transcript; re-run (one retry is automatic).

What ships with it: 1 file

9.1 KB alongside SKILL.md, 1 of them executable

scripts/

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