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 yideng966/LightAgent --skill image-generationgit clone --depth 1 https://github.com/yideng966/LightAgentWrote 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/yideng966/lightagent/image-generation)<a href="https://agentmods.dev/skills/yideng966/lightagent/image-generation"><img src="https://agentmods.dev/badge/skills/yideng966/lightagent/image-generation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yideng966/lightagent/image-generation"><img src="https://agentmods.dev/badge/skills/yideng966/lightagent/image-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.01441 |
| Opus 5.5 | $0.00016 | $0.00576 |
| Sonnet 5.5 | $0.00008 | $0.00288 |
| Haiku 4.5 | $0.00004 | $0.00144 |
Grade A, and why
image-generation 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 1mo ago.
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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Generation
Generate and edit images using AI models. The script automatically picks a backend based on which API keys are configured — you don't need to specify a model unless the user explicitly names one.
Supported models (passed via model only when the user asks for a specific one):
- OpenAI —
gpt-image-2,gpt-image-1 - Gemini Nano Banana —
nano-banana-2,nano-banana-pro,nano-banana - Seedream (Volcengine Ark) —
seedream-5.0-lite,seedream-4.5 - Qwen (DashScope) —
qwen-image-2.0,qwen-image-2.0-pro - MiniMax —
image-01
Usage
Run scripts/generate.py with a UTF-8 JSON request file. The path is relative to this skill's base_dir.
- Use the
writetool to create a uniquely named request file under the workspacetmp/directory. Do not create it with shellechobecause prompts can contain shell metacharacters. - Run the script with that file:
python "<base_dir>/scripts/generate.py" --json-file "<workspace>/tmp/image-generation-request-<unique>.json"
On Windows, the bash tool runs through cmd.exe: never pass inline JSON wrapped in single quotes. cmd.exe does not treat single quotes as argument delimiters and will corrupt the JSON. The --json-file form works on every supported platform and is the preferred form. Inline JSON remains supported on POSIX shells for backward compatibility only.
Set bash timeout to at least 600 seconds, as image generation can take 30–200s per provider, and the script may try multiple providers sequentially.
Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
prompt |
string | yes | — | Image description |
image_url |
string / list | no | null | Input image(s) for editing: local file path or URL. Multi-image fusion is supported (pass a list) |
quality |
string | no | auto | low / medium / high (only some backends honour this) |
size |
string | no | auto | 512 / 1K / 2K / 3K / 4K, or pixel value (1024x1024) |
aspect_ratio |
string | no | null | 1:1 / 3:2 / 2:3 / 16:9 / 9:16 / 21:9 (some backends also support extreme ratios like 1:4 / 8:1) |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 132 lines · 41 tokens per session scan A e9e374766d92
image-generation is a skill published in the GitHub repository yideng966/LightAgent (22 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 1,441 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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