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 yunshu0909/yunshu_skillshub --skill logo-designgit clone --depth 1 https://github.com/yunshu0909/yunshu_skillshubWrote 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/yunshu0909/yunshu_skillshub/logo-design)<a href="https://agentmods.dev/skills/yunshu0909/yunshu_skillshub/logo-design"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/logo-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/yunshu0909/yunshu_skillshub/logo-design"><img src="https://agentmods.dev/badge/skills/yunshu0909/yunshu_skillshub/logo-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 | $0.00096 | $0.02533 |
| Opus 5.5 | $0.00038 | $0.01013 |
| Sonnet 5.5 | $0.00019 | $0.00507 |
| Haiku 4.5 | $0.00010 | $0.00253 |
Grade A, and why
logo-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 18d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Logo 设计与交付
运行环境：必须在 Codex 中使用。 出图、参考图编辑和品牌场景图依赖 Codex 的图像生成工具（imagegen）。在 Claude Code 等没有图像生成能力的环境里被触发时，不要用 SVG/代码拼图冒充概念稿，直接告知用户切到 Codex 执行；只做研究、讨论或诊断且不需要出图时可继续。
把用户的偏好变成稳定的图形，再把图形变成可用资产。根据当前证据进入合适阶段，不把每次调用都变成完整品牌项目。
常见路线是：定位与用途 → 审美探索 → 方向探索 → 分层收敛 → 应用验证 → 精修与组合 → 资产交付。已有方案直接从对应阶段继续；应用问题优先退回构图，方向问题才退回探索。用户主动要求讨论时先讨论，不用大量出图代替共同理解。
先确定现在要解决什么
读取当前对话、用户选择及已有图稿。查看实际参考图，不凭文件名判断。简短说清本轮目标及会保留什么。
| 当前请求或证据 | 本轮动作 | 完成标准 |
|---|---|---|
| 新产品，尚无方向 | 补齐关键定位，做差异明确的视觉探索 | 用户能比较并指出喜欢的方向/特征 |
| 要求研究，或多轮都不满意 | 查询一手设计案例，提出可检验的诊断 | 区分方向、造型、构图和呈现问题；给出下轮验证变量 |
| 已选某个方向或版本 | 固定基准，做受控精修 | 能看出哪个改动有效，保留原版可回退 |
| 要一套品牌效果 | 用同一母版展示组合与场景 | 风格一致，标明尚未生产化的部分 |
| 要直接使用、保存或导出 | 确立矢量/高清母版，导出并检查 | 有实际文件、用途说明和可访问路径 |
用户只要研究时不要自动生成图；已选 A 时不要重新打开所有方向；已请求导出时不要停在展示板。已知的信息不重复问。缺失信息只问会改变下一步的内容，并继续不依赖答案的工作。
用户给出的数量和范围优先于默认探索方式。“随机做一个”表示从合理的创意空间里选一个有依据的设计命题直接完成，不要求再做多方向；随机不是无理由拼形。“做三个不同风格”则在形式类别上拉开差异，例如字标/字母、抽象符号、角色或徽章，而不是把同一构图换三种颜色。
最小设计状态
短任务可保留在对话；跨轮或开始文件交付时写入该项目的设计记录。只保存必要内容：
- 产品与用途：服务谁、核心作用；主要出现在哪个尺寸和载体。
- 想表达的性格：少量可区分的词，以及明显不喜欢的感觉。
- 基准：具体文件与版本标识；若来自对照板，明确是哪一格。
- 已锁定特征：来自用户明确选择的轮廓、颜色关系、表情等。
- 分层状态：分别记录表达方向、轮廓、内部元素、颜色关系、构图、字标为已选/暂定/待验证；一层的选择不自动批准其他层。
- 当前假设与变量：本轮为什么改、只改变什么。
- 结果：用户说了什么、哪些解释仍只是设计师判断、哪些版本被否定。
不要把“喜欢这张图”扩张为批准新字体、新口号、应用替换或发布。不要把模型自己推荐的版本记录成用户选择。
首次概念里由设计师补出的颜色、字体方向、标志类型和使用场景都属于设计假设；在用户明确选择前不要记成品牌规范。
定位与研究
定位用于选择表达，不要求 Logo 把功能逐项画出来。区分角色/吉祥物、品牌标志、字标组合、应用图标：可共享身份，但不必共享完整构图。
用户要求联网研究时，优先查品牌官方规范、设计公司原始案例和设计师复盘。每个案例提取：问题、做法、适用条件；随后说明对当前作品的推论。给一手链接，区分资料事实和自己的视觉判断。案例数量以能回答问题为准，不堆参考墙。
需要研究思路时按问题读取 references/design-research.md，将来源事实、可迁移原则、本轮验证动作分开。研究结束必须落到一个设计决定或下一轮对照；历史案例不代表当前平台规范，遇到跳转/失效不假装仍可核验。
借鉴方法与约束，不复刻辨识性轮廓或构图。不能凭“由 AI 生成”宣称原创或已排除近似商标。一般探索不扩张为法律审查；用户要求近似检索时再做并说明范围。
页面设计风格可以提供产品背景，但不能直接推导 Logo 必须是什么样。不要把某类产品默认等同于渐变、星芒、代码括号或机器人。
探索与反馈诊断
需求含糊、用户想讨论或难以描述审美时，先读 references/co-design.md。每轮给用户可判断的具体对象，围绕一个主要问题交流；不用长问卷，也不让用户独自承担“说明白审美”的工作。
首次出图或批量探索前读 references/exploration.md，其中包含生成前的设计状态和交付检查。
What ships with it
5 files 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.
- 18d ago Changed · +3 lines 38451338b9ce
- 1mo ago First seen · 103 lines · 96 tokens per session scan A b4d9714e828c
logo-design is a skill published in the GitHub repository yunshu0909/yunshu_skillshub (784 stars, last pushed 13d ago), licensed MIT. It adds 96 tokens to every session and 2,533 once invoked, about $0.0004 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 2026-09-20.
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