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 skills add lfyxhappy/lfcode --skill imagemakergit clone --depth 1 https://github.com/lfyxhappy/lfcodeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lfyxhappy/lfcode/imagemaker)<a href="https://agentmods.dev/skills/lfyxhappy/lfcode/imagemaker"><img src="https://agentmods.dev/badge/skills/lfyxhappy/lfcode/imagemaker.svg" alt="Measured on agentmods" height="20"></a>What 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 5.1 | $0.00037 | $0.00303 |
| Opus 5 | $0.00018 | $0.00151 |
| Sonnet 5 | $0.00007 | $0.00061 |
| Haiku 4.5 | $0.00004 | $0.00030 |
Grade A, and why
imagemaker 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.
What it actually says
ImageMaker
Use imagemaker_generate to create images from a prompt. Include the desired visual content, style, composition, lighting, aspect ratio, and exclusions in the prompt or negative prompt. Do not invent an API key or expose provider credentials.
To revise an image created earlier in this conversation, use imagemaker_edit with its exact image_id from the generation result and a concise edit instruction. Image editing currently requires the configured OpenAI-compatible image provider; state that limitation clearly instead of silently switching providers.
If generation reports that no provider is configured, ask the user to open the plugin page, choose a provider, and save its API key. Supported profiles include OpenAI and compatible endpoints, Azure OpenAI, Stability AI, Replicate, BFL/FLUX, Gemini/Imagen, DashScope/Wanxiang, Volcengine Ark/Doubao, and declarative custom REST endpoints.
Generated images are saved in the plugin gallery and returned as rich conversation cards with image attachments. Preserve the user's prompt and provider choice when revising an image unless they request changes. There is no separate ImageMaker project or workspace.
For custom REST providers, use only declarative URL, method, headers, JSON body, and response-path configuration. Never execute user-provided scripts.
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 · 17 lines · 37 tokens per session scan A 010c8d9dafa5
imagemaker is a skill published in the GitHub repository lfyxhappy/lfcode (2 stars, last pushed 4d ago), licensed MIT. It adds 37 tokens to every session and 303 once invoked, about $0.0002 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 2026-09-05.
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