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 majiang213/OpenClaw-MAS --skill cmd_gan_designgit clone --depth 1 https://github.com/majiang213/OpenClaw-MASWrote 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/majiang213/openclaw-mas/cmd_gan_design)<a href="https://agentmods.dev/skills/majiang213/openclaw-mas/cmd_gan_design"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/cmd_gan_design/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/majiang213/openclaw-mas/cmd_gan_design"><img src="https://agentmods.dev/badge/skills/majiang213/openclaw-mas/cmd_gan_design.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00030 | $0.00317 |
| Opus 5 | $0.00015 | $0.00159 |
| Sonnet 5 | $0.00006 | $0.00063 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
cmd_gan_design 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 6d 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.
This is a copy
89% identical to cmd_gan_build — 23 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Run specialist agents in sequence: gan-generator → gan-evaluator.
Include in the task payload:
- Project path (the absolute path the user provided as the first argument)
- The user's full request and build/design brief
- Any flags or configuration options (max iterations, pass threshold, etc.)
- Relevant codebase context
Execute specialist agents in sequence: gan-generator → gan-evaluator
- Reply to the user briefly, then call sessions_spawn:
{
"agentId": "gan-generator",
"sessionKey": "gan-generator",
"task": "<task description with full context from previous step>",
"runTimeoutSeconds": 0
}
Wait for this agent to complete before proceeding.
- Reply to the user briefly, then call sessions_spawn:
{
"agentId": "gan-evaluator",
"sessionKey": "gan-evaluator",
"task": "<task description with full context from previous step>",
"runTimeoutSeconds": 0
}
Wait for this agent to complete before proceeding.
Do not spawn the next agent until the current one completes. Do not spawn agents in parallel. After all agents complete, return the final result to the user.
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.
- 6d ago First seen · 47 lines · 30 tokens per session scan A 9ed5dd82ebfb
cmd_gan_design is a skill published in the GitHub repository majiang213/OpenClaw-MAS (5 stars, last pushed 5mo ago), licensed MIT. It adds 30 tokens to every session and 317 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to cmd_gan_build, differing in 23 lines, and is treated as a copy.
Other skills, from other repositories
presentation-creator
Builds decks with a story spine, house visual system, setting-specific density, and speaker notes. Use when asked to "create a presentation", "write a pitch deck", or "turn this doc into slides". Defaults to Marp; use an available presentation tool for editable PowerPoint. For product UI use ui-design.
lark-slides
A tool for creating and editing Feishu slide presentations, including their pages and content. Feishu is a workplace collaboration platform.
baoyu-infographic
A generator for infographics that combines one of 21 information layouts with one of 21 visual styles.
baoyu-infographic
A toolkit for creating pictures and text banners from ordinary keyboard characters, called ASCII art. It supports local command-line tools and some free online services for text, images, and related artwork.
beautiful-feishu-whiteboard
A library of 37 curated colour palette styles for building beautiful, editable Feishu / Lark (飞书) whiteboards from SVG. Use this whenever the user wants to create or draw a Feishu whiteboard, infographic, diagram, poster, or visual explainer and wants it to look polished, on brand, or in a particular aesthetic, or…
canvas-design
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.