MBB Management Consultant AI Skill and Plugin for LLMs

The most comprehensive open-source consulting intelligence layer for any LLM. A structured, hypothesis-driven consulting knowledge base that works with Claude, Codex, Gemini, GitHub Copilot, Cursor, Ollama, and any other AI assistant. Built for MBA students, case interview candidates, business professionals, and anyone who needs to think at McKinsey / Bain / BCG level.

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TL;DR: Install this skill and your AI assistant (Claude, Codex, Gemini, Copilot, Ollama, or any other LLM) works like an MBB-grade management consultant, coaching you through case interviews, applying strategy frameworks, sizing markets, and turning messy business problems into board-ready answers. 138 reference modules distilled from public consulting knowledge. Free and open-source; contributions welcome.

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Install

Claude Code, one command:

/plugin marketplace add DogInfantry/claude-skill-management-consultant-B1
/plugin install management-consultant

Works in any other AI agent too: Codex, GitHub Copilot, Gemini, Cursor, and Ollama auto-load the skill from AGENTS.md / GEMINI.md / .github/copilot-instructions.md / Modelfile, and any LLM can use it by attaching skill/SKILL.md. Full walkthrough and manual setup: Quick Start · INSTALL.md.

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What Is This?

The MBB Management Consultant AI Skill is a structured knowledge system that installs into your AI assistant (Claude, Codex, Gemini, GitHub Copilot, Ollama, and more), giving it the cognitive architecture of a senior strategy consultant. It is not a simple prompt; it is 138 reference modules, organized around 5 knowledge pillars, covering every dimension of consulting work from MECE issue trees and Pyramid Principle communication to M&A due diligence, GenAI enterprise strategy, and case interview coaching.

Unlike generic AI prompts, this skill:

• Applies hypothesis-driven thinking: forms a point of view before gathering data
• Structures every problem MECE (Mutually Exclusive, Collectively Exhaustive)
• Leads every output with the governing thought (Pyramid Principle)
• Draws from 10+ industry reference files and 138 deep-knowledge modules
• Follows the MBB operating model: Frame → Structure → Analyse → Synthesise → Deliver

Compatible with: Claude (Code, Free, Pro, Teams), OpenAI Codex, Google Gemini, GitHub Copilot, Cursor, Ollama (local models), and any other LLM you can paste context into.

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How It Works

flowchart LR
    A["🔍 Problem Brief"] --> B["1. Frame"]
    B --> C["2. Structure"]
    C --> D["3. Analyse"]
    D --> E["4. Synthesise"]
    E --> F["5. Deliver"]

    B -.->|reads| G[("138 Reference Files")]
    C -.-> G
    D -.-> G
    E -.-> G
    F -.->|"Board-ready output"| H["✅ Client Value"]

Frame → Structure → Analyse → Synthesise → Deliver. Every problem flows through the same consulting operating system, drawing from 5 knowledge pillars and 138 reference modules.

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Knowledge Architecture

The 138 reference files are organized across five knowledge pillars: