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 renky1025/agent-skills --skill mckinsey-covergit clone --depth 1 https://github.com/renky1025/agent-skillsWrote 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/renky1025/agent-skills/mckinsey-cover)<a href="https://agentmods.dev/skills/renky1025/agent-skills/mckinsey-cover"><img src="https://agentmods.dev/badge/skills/renky1025/agent-skills/mckinsey-cover/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/renky1025/agent-skills/mckinsey-cover"><img src="https://agentmods.dev/badge/skills/renky1025/agent-skills/mckinsey-cover.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 | $0.00115 | $0.05492 |
| Opus 5 | $0.00057 | $0.02746 |
| Sonnet 5 | $0.00023 | $0.01098 |
| Haiku 4.5 | $0.00012 | $0.00549 |
Grade A, and why
mckinsey-cover 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 12d 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 — 734 lines — stays where its author put it; the contents beside it link to each section on GitHub.
mckinsey-cover: 麦肯锡风格封面图片生成
基于 Adrian Punk 原创「麦肯锡风格提示词」，生成具有顶级咨询公司视觉质感的高级封面或信息图。
Outcome Contract
- Outcome：基于用户输入的主题词和用途，生成一张麦肯锡风格高级视觉作品
- Done when：图片已通过 ImageGen 生成并保存到
~/Downloads/mckinsey-cover/ - Evidence：白底深蓝配色、文字重构、商业隐喻、极简咨询风格
使用方法
/mckinsey-cover <主题词> [--usage=<用途>] [--subtitle=<副标题>] [--ratio=<画幅>] [--lang=<语言>]
| 参数 | 说明 | 默认值 |
|---|---|---|
<主题词> |
封面/信息图的核心主题，必填 | — |
--usage |
用途，决定封面逻辑 or 信息图逻辑 | cover |
--subtitle |
副标题，可留空 | 空 |
--ratio |
画幅比例：5:2 / 16:9 / 4:5 / 3:4 / 1:1 |
5:2 |
--lang |
语言：中文 / 英文 / 中英混排 |
中文 |
--context |
补充语境（行业背景/目标受众/使用场景/情绪倾向） | 空 |
--ban |
禁用元素 | 空 |
用途选项
封面类：cover(X封面) / ppt(PPT封面) / report(商业报告) / portfolio(作品集) / wechat(公众号)
信息图类：infographic(信息图) / consulting(咨询分析) / methodology(方法论) / flowchart(流程图) / matrix(矩阵图)
执行步骤
第一步：解析输入
- 提取主题词（必填）
- 映射
--usage到提示词中的用途描述（见表） - 填充其余参数默认值
- 如果主题过长（> 30 字），标记以便提示词中的"长标题提炼机制"生效
--usage |
提示词中对应的用途 |
|---|---|
cover |
X封面 |
ppt |
PPT封面 |
report |
商业报告封面 |
portfolio |
作品集封面 |
wechat |
公众号封面 |
infographic |
信息图 |
consulting |
咨询分析页 |
methodology |
方法论图 |
flowchart |
流程图 |
matrix |
矩阵图 |
第二步：填充提示词模版
将用户输入填入下方提示词模版的 {{}} 占位符中，生成完整的 ImageGen prompt：
{{主题词}}→ 用户输入的主题{{副标题}}→ 用户输入的副标题，无则留空字符串{{画幅比例}}→--ratio参数值（如5:2）{{语言}}→--lang参数值（如中文）{{用途}}→ 映射后的用途描述（如X封面）{{补充语境}}→--context参数值，无则留空{{禁用元素}}→--ban参数值，无则留空
第三步：调用 ImageGen
填充完成后，将完整提示词传给 ImageGen。提示词本身已包含角色设定、分流规则、设计规范和最终指令。
{
"prompt": "<第二步生成的完整提示词>",
"size": "1024x1536",
"quality": "high",
"output_dir": "~/Downloads/mckinsey-cover"
}
尺寸映射：
--ratio |
size |
|---|---|
5:2 |
1536x614 |
16:9 |
1536x864 |
4:5 |
1024x1280 |
3:4 |
1152x1536 |
1:1 |
1024x1024 |
第四步：展示结果
使用 present_files 展示生成的图片。
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.
- 12d ago First seen · 734 lines · 115 tokens per session scan A d7d4d4b7ec83
mckinsey-cover is a skill published in the GitHub repository renky1025/agent-skills (11 stars, last pushed 2d ago), licensed MIT. It adds 115 tokens to every session and 5,492 once invoked, about $0.0006 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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