How do I install the Consultant Bcg skill?

Run npx skillmds@latest add nahisaho/consultant-bcg in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Consultant Bcg safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Consultant Bcg?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Consultant Bcg free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Consultant Bcg?

nahisaho (@nahisaho) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Consultant Bcg by nahisaho — Agent Skill

Name: Consultant Bcg
Author: nahisaho

Consultant Bcg

BCG (Boston Consulting Group) style consulting skill for deep research and analysis. Features Growth-Share Matrix, Experience Curve, Strategy Palette, Hypothesis-Driven Approach, TSR Analysis, Advantage Matrix, and Bionic Company Framework. 4-phase workflow: Purpose Discovery → Deep Research → Framework Analysis → Report Writing. Supports Deep Research MCP for enhanced web research capabilities.

nahisaho Updated Sep 17, 2026

File contents

Consultant BCG (Boston Consulting Group-Style Consulting)

Use This Skill When

A strategy, portfolio, or transformation problem needs BCG-style framing.
Growth, competitive advantage, TSR, or bionic transformation analysis must be structured into a staged workflow.
The engagement requires saved, reusable artifacts rather than chat-only analysis.

Local Resources

prompts/: phased flows for discovery, research, framework analysis, and reporting.
skills/: nested Agent Skills including orchestrator/SKILL.md for routing and framework application.
Use deep-research MCP when available for structured external research.

Required Inputs

Client objective, portfolio scope, and strategic decision to support.
Available evidence, assumptions, timing, and review constraints.
Required report format, metrics, and decision criteria.

Workflow

Confirm scope, evidence path, and the artifact set to save.
Route through the orchestrator or local helpers only when they materially improve the current task.
Save analyses, intermediate outputs, and recommendations to files instead of leaving results in chat.
Verify assumptions, traceability, and recommendation quality before finalizing conclusions.
Append skill selection, handoff I/O, and file writes to logs/process-log.jsonl when the execution harness requires trace logging.

Deliverables

report.md: strategic question, method, framework output, recommendation, and file inventory.
results/: matrices, scorecards, portfolio classifications, and structured evidence summaries.
figures/: English-only strategy visuals, portfolio charts, or comparison plots when needed.
data/: normalized source material when transformation occurs.

Quality Gates

The chosen BCG-style framework matches the client objective and evidence quality.
Assumptions, calculations, and recommendation logic are traceable.
Final outputs contain actionable next steps and saved supporting artifacts.
report.md and, when used, logs/process-log.jsonl reference generated files.

---name: consultant-bcgdescription: BCG (Boston Consulting Group) style consulting skill for deep research and analysis. Features Growth-Share Matrix, Experience Curve, Strategy Palette, Hypothesis-Driven Approach, TSR Analysis, Advantage Matrix, and Bionic Company Framework. 4-phase workflow: Purpose Discovery → Deep Research → Framework Analysis → Report Writing. Supports Deep Research MCP for enhanced web research capabilities.---# Consultant BCG (Boston Consulting Group-Style Consulting)BCG (Boston Consulting Group) style consulting skill for deep research and analysis. Features Growth-Share Matrix, Experience Curve, Strategy Palette, Hypothesis-Driven Approach, TSR Analysis, Advantage Matrix, and Bionic Company Framework. 4-phase workflow: Purpose Discovery → Deep Research → Framework Analysis → Report Writing. Supports Deep Research MCP for enhanced web research capabilities.## Use This Skill When- A strategy, portfolio, or transformation problem needs BCG-style framing.- Growth, competitive advantage, TSR, or bionic transformation analysis must be structured into a staged workflow.- The engagement requires saved, reusable artifacts rather than chat-only analysis.## Local Resources- `prompts/`: phased flows for discovery, research, framework analysis, and reporting.- `skills/`: nested Agent Skills including `orchestrator/SKILL.md` for routing and framework application.- Use `deep-research` MCP when available for structured external research.## Required Inputs- Client objective, portfolio scope, and strategic decision to support.- Available evidence, assumptions, timing, and review constraints.- Required report format, metrics, and decision criteria.## Workflow1. Confirm scope, evidence path, and the artifact set to save.2. Route through the orchestrator or local helpers only when they materially improve the current task.3. Save analyses, intermediate outputs, and recommendations to files instead of leaving results in chat.4. Verify assumptions, traceability, and recommendation quality before finalizing conclusions.5. Append skill selection, handoff I/O, and file writes to `logs/process-log.jsonl` when the execution harness requires trace logging.## Deliverables- `report.md`: strategic question, method, framework output, recommendation, and file inventory.- `results/`: matrices, scorecards, portfolio classifications, and structured evidence summaries.- `figures/`: English-only strategy visuals, portfolio charts, or comparison plots when needed.- `data/`: normalized source material when transformation occurs.## Quality Gates- The chosen BCG-style framework matches the client objective and evidence quality.- Assumptions, calculations, and recommendation logic are traceable.- Final outputs contain actionable next steps and saved supporting artifacts.- `report.md` and, when used, `logs/process-log.jsonl` reference generated files.

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