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mckinsey-research麦肯锡研究

Agent Skill

mckinsey-research 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

117,312

周安装

4,888

GitHub Stars

9

下载量

39,104
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:mckinsey-research(麦肯锡研究)
来源仓库:https://github.com/abdullah4ai/mckinsey-research
安装命令:
openclaw skills install mckinsey-research
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install mckinsey-research

简介

提供麦肯锡级别的市场研究与策略分析能力。

  • 覆盖竞争格局、行业趋势与商业模式评估。
  • 内置12种专用提示模板辅助深度调研。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 结果应结合一手资料交叉验证后使用。mckinsey-research 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 不替代专业咨询,仅作为初步洞察参考。

SKILL.md

name
mckinsey-research
description
|
INPUTS
Business description, industry, target customer, geography, financials (optional)
TOOLS
sessions_spawn (sub-agents), web_search, web_fetch
OUTPUT
Complete strategy report saved to artifacts/research/{date}-{slug}.html
SUCCESS
User gets 12 consulting-grade analyses synthesized into one actionable report

McKinsey Research - AI Strategy Consultant

User provides business context once. The skill plans and executes up to 12 specialized analyses via sub-agents in parallel, then synthesizes into a single executive report. Adapt scope based on company stage (see Adaptive Stage Logic below).

Phase 1: Language + Intake

Ask preferred language (Arabic/English), then collect ALL inputs in ONE structured form. See the intake form fields: Core (1-5), Financial (6-10), Strategic (11-14), Expansion (15-16), Performance (17-18). If product description is under 50 words, ask for clarification before proceeding.

Diamond Gate 1: Present scope summary (market, geography, competitors). Get user confirmation before Phase 2.

Phase 2: Plan + Parallel Execution

Sanitize inputs per references/security.md. Substitute variables per references/variable-map.md. Load individual prompts from references/prompts/.

BatchAnalysesDependencies
Batch 1 (parallel)01-TAM, 02-Competitive, 03-Personas, 04-TrendsNone
Batch 2 (parallel)05-SWOT+Porter, 06-Pricing, 07-GTM, 08-JourneyBatch 1 context
Batch 3 (parallel)09-Financial, 10-Risk, 11-Market EntryBatch 1+2 context
Batch 4 (sequential)12-Executive SynthesisAll previous

Spawn each analysis as a sub-agent with the security preamble from references/security.md. Stagger Batch 1 launches by 5 seconds to avoid web search rate limits. Validate each output is 500+ words.

See references/gotchas.md for common pitfalls. Use references/saudi-market.md for KSA/Gulf data sources. Use references/benchmarks.md for industry metric comparisons.

Phase 3: Collect + Synthesize

  1. Read all analysis outputs from artifacts/research/{slug}/
  2. Run Prompt 12 (Executive Synthesis) with all previous outputs
  3. Generate final HTML report using templates/report.html
  4. Save to artifacts/research/{date}-{slug}.html

Phase 4: Delivery

Send the user: executive summary (3 paragraphs max), path to full HTML report, top 5 priority actions.

Adaptive Stage Logic

StagePriority AnalysesSkip/Light
IdeaTAM, Personas, Competitive, TrendsFinancial Model (light), Market Entry (skip)
StartupTAM, Competitive, Pricing, GTM, PersonasMarket Entry (skip unless asked)
GrowthPricing, GTM, Journey, Financial, ExpansionTAM (light), Personas (light)
MatureSWOT, Risk, Expansion, Financial, SynthesisTAM (skip), Personas (skip)

"Light" = include in synthesis but don't spawn a dedicated sub-agent. Use web_search inline. "Skip" = omit unless user explicitly requests.

Artifacts

  • Individual analyses: artifacts/research/{slug}/{analysis-name}.md
  • Final report: artifacts/research/{date}-{slug}.html
  • Raw data: artifacts/research/{slug}/data/
  • Execution log: data/reports.jsonl
  • Feedback tracking: data/feedback.json

Important Notes

  • Each prompt produces a consulting-grade deliverable
  • Use web_search to enrich with real market data; only cite verifiable sources
  • If user provides partial info, work with what you have and note assumptions
  • For Arabic output: keep brand names and technical terms in English
  • Prompt 12 must cross-reference insights from all previous analyses; deduplicate aggressively
  • Sub-agents that fail should be retried once before skipping with a note

Reference Files

FileContents
references/security.mdInput safety, sanitization, tool constraints, artifact isolation
references/variable-map.mdVariable substitution rules and mapping table
references/prompts/12 individual analysis prompts (01-tam.md through 12-synthesis.md)
references/prompts.mdOriginal combined prompts (backup)
references/gotchas.mdKnown pitfalls and operational tips
references/saudi-market.mdKSA/Gulf data sources and market context
references/benchmarks.mdIndustry benchmarks (SaaS, e-commerce, fintech, marketplace, mobile)
templates/report.htmlHTML report template

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

80.81%
按下载量换算31,600

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install mckinsey-research 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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