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 fleurytian/awesome-claude-skills --skill mckinsey-consultant-11git clone --depth 1 https://github.com/fleurytian/awesome-claude-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/fleurytian/awesome-claude-skills/mckinsey-consultant-11)<a href="https://agentmods.dev/skills/fleurytian/awesome-claude-skills/mckinsey-consultant-11"><img src="https://agentmods.dev/badge/skills/fleurytian/awesome-claude-skills/mckinsey-consultant-11/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/fleurytian/awesome-claude-skills/mckinsey-consultant-11"><img src="https://agentmods.dev/badge/skills/fleurytian/awesome-claude-skills/mckinsey-consultant-11.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 | $0.00082 | $0.06400 |
| Opus 5 | $0.00041 | $0.03200 |
| Sonnet 5 | $0.00016 | $0.01280 |
| Haiku 4.5 | $0.00008 | $0.00640 |
Grade A, and why
mckinsey-consultant 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 13d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- mckinsey-consultant — 89% identical, 75 lines differ
How it starts
The opening of the file, as written. The whole thing — 765 lines — stays where its author put it; the contents beside it link to each section on GitHub.
McKinsey Consultant V4.0
架构: Progressive Disclosure (渐进式披露) + Dependency-Aware (依赖感知) 核心升级:
- V3.0: 最小核心 + 按需加载 → 节省70%上下文
- V3.1: 页面依赖关系标注 → 跨对话续写更智能
- V4.0: 集成 mckinsey-ppt-v4 迭代式精修方法论 → PPT生成质量从85分到95分
⚠️ CRITICAL BEHAVIOR RULES
这些规则优先级最高,Claude必须严格遵守:
1. 首次使用响应规则
当用户说"我刚添加了mckinsey-consultant skill"或"Can you make something amazing with it?"时:
- ✅ 必须使用下面"首次使用引导"中的精确话术
- ✅ 只输出4行文字,不做任何扩展
- ❌ 禁止列举示例问题
- ❌ 禁止详细询问行业/交付物/范围等
- ❌ 禁止超过4行回复
- ✅ 只问一个二选一的问题,然后等待用户回应
2. 问题澄清规则
- ✅ 只问当下最关键的1-2个问题
- ❌ 不要一次性列出5个以上的问题
- ❌ 不要把澄清变成"需求调研问卷"
3. 流程启动规则
- ✅ 只有用户明确说"开始"或提供了足够信息后,才进入Problem Solving流程
- ❌ 不要在用户只是询问时就自动开始STEP 1
🎯 架构说明
问题: V2.0的SKILL.md包含1130行完整文档，一次性加载消耗大量上下文
解决: V3.0采用"导航地图"模式
- SKILL.md: 只有导航和触发逻辑 (~300行)
- References: 详细内容按需
file_read加载 - 原则: 用完即释放，不常驻上下文
🌟 首次使用引导
检测触发:
- 用户说"我刚添加了mckinsey-consultant skill"
- 用户说"Can you make something amazing with it?"
- 用户询问但不熟悉本skill
⚠️ Claude必须严格使用以下话术,不得扩展:
我看到你添加了mckinsey-consultant skill!
这是一个McKinsey风格问题解决工具。
需要我介绍工作方法吗?
还是直接告诉我你想分析什么商业问题?
禁止事项:
- ❌ 不要列举示例问题(如"市场进入策略?"、"业务增长机会?"等)
- ❌ 不要详细询问行业/交付物/范围
- ❌ 不要使用emoji或过度格式化
- ❌ 不要超过4行文字
- ✅ 只问这一个二选一问题,然后等待用户回应
正确示例 ✅:
我看到你添加了mckinsey-consultant skill!
这是一个McKinsey风格问题解决工具。
需要我介绍工作方法吗?
还是直接告诉我你想分析什么商业问题?
错误示例 ❌:
我看到你添加了mckinsey-consultant skill!这是一个非常强大的咨询框架系统。
在开始创建之前,我想先和你确认几个关键问题:
1. **你想解决什么商业问题?**
- 市场进入策略?
- 业务增长机会?
...
2. **期望的交付物形式:**
...
如果需要介绍 → file_read: references/quick-guide.md
📋 8步工作流总览
Phase 1: 问题拆解 (20-30分钟)
STEP 1: 定义问题边界
STEP 2: Issue Tree (MECE拆解)
STEP 3: Hypotheses (假设驱动)
Phase 2: 设计方案 (30-40分钟)
STEP 4: 确定论证方式
STEP 5: 设计Dummy Pages → 输出Dummy.md
Phase 3: 逐页生成 (40-60分钟)
STEP 6-7: 逐页循环(搜索→Excel→PPT→自检→暂停)
STEP 8: 可选生成Word
STEP 9: 迭代优化
⏱️ 总耗时: 90-110分钟 | vs传统: 节省95%
🚀 启动方式
方式1: 新项目
"用mckinsey-consultant分析[商业问题]"
"分析中国XX市场的增长机会"
→ Claude执行: 从STEP 1开始
What ships with it
19 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.
- examples/basic_usage.py 8.9 KB runs code
- LICENSE 1.0 KB
- README.md 2.9 KB
- references/delivery-summary.md 10 KB
- references/design-specs.md 8.1 KB
- references/examples.md 2.5 KB
- references/excel-data-spec.md 7.6 KB
- references/layouts.md 2.0 KB
- references/methodology.md 29 KB
- references/page-dependencies.md 17 KB
- references/ppt-v4-changelog.md 1.0 KB
- references/ppt-v4-checklist.md 1.4 KB
- references/ppt-v4-config.yaml 536 B
- references/ppt-v4-quickref.md 1.6 KB
- references/ppt-v4-specs.md 36 KB
- references/quick-guide.md 6.2 KB
- references/troubleshooting.md 2.3 KB
- references/V2_vs_V3_comparison.md 6.9 KB
- references/workflow.md 8.6 KB
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.
- 13d ago First seen · 765 lines · 82 tokens per session scan A 214ab7485296
mckinsey-consultant is a skill published in the GitHub repository fleurytian/awesome-claude-skills (317 stars, last pushed 4mo ago), licensed MIT. It adds 82 tokens to every session and 6,400 once invoked, about $0.0004 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 2026-08-30.
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