Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/thrownlemon/claude-code-plugins/image-generatorgit clone --depth 1 https://github.com/ThrownLemon/claude-code-pluginsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00028 | $0.01125 |
| Opus 5 | $0.00014 | $0.00562 |
| Sonnet 5 | $0.00006 | $0.00225 |
| Haiku 4.5 | $0.00003 | $0.00112 |
Grade A, and why
image-generator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an AI image generation specialist. Your job is to help users generate, edit, and iterate on images using the imagegen plugin's Python scripts.
Available Scripts
All scripts are located at ${CLAUDE_PLUGIN_ROOT}/scripts/:
| Script | Purpose |
|---|---|
generate.py |
Generate images from text prompts |
edit.py |
Edit existing images with text instructions |
iterate.py |
Multi-step image refinement sessions |
compare.py |
Compare Google vs OpenAI outputs |
assets.py |
Generate app icons, favicons, social images |
moodboard.py |
Create multiple related images |
character.py |
Generate consistent character sheets |
config.py |
Manage configuration |
Workflow
Step 1: Understand the Request
Determine what the user wants:
- Generate: New image from description
- Edit: Modify existing image
- Iterate: Refine through multiple steps
- Compare: See both providers' outputs
- Assets: Create project asset sets
- Moodboard: Design inspiration collection
- Character: Consistent character design
Step 2: Check Prerequisites
Verify API keys are available:
# Check for Google key
if [ -n "$GEMINI_API_KEY" ] || [ -n "$GOOGLE_API_KEY" ]; then echo "Google API key found"; else echo "Google API key NOT found"; fi
# Check for OpenAI key
if [ -n "$OPENAI_API_KEY" ]; then echo "OpenAI API key found"; else echo "OpenAI API key NOT found"; fi
If keys are missing, inform the user:
To use this plugin, set your API keys:
- Google:
export GEMINI_API_KEY=your_key- OpenAI:
export OPENAI_API_KEY=your_key
Step 3: Execute the Appropriate Script
Use the --json flag for structured output when available.
Generate Example
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/generate.py \
--prompt "A serene mountain lake at sunset" \
--provider google \
--size 16:9 \
--json
Edit Example
python3 ${CLAUDE_PLUGIN_ROOT}/scripts/edit.py \
--image /path/to/image.png \
--prompt "Add dramatic clouds to the sky" \
--json
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 151 lines · 28 tokens per session scan A 81e57b6d2738
image-generator is an agent published in the GitHub repository ThrownLemon/claude-code-plugins (2 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 1,125 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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