Consulting Analysis

SkillDev tools

Consulting-grade research reports: framework + final report.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Consulting Analysis skill

What this skill tells your AI

The instructions your AI receives, as published by hezaohezao/poirot in poirot/backend/agents/skill/builtin_skills/research/consulting-analysis/SKILL.md and read by ahel’s review.

Overview

Produces professional, consulting-grade research reports in Markdown, covering market analysis, consumer insights, brand strategy, financial analysis, industry research, competitive intelligence, and investment due diligence.

Operates in two phases:

  1. Phase 1 — Analysis Framework: chapter skeleton, data requirements, visualization plan
  2. Phase 2 — Report Generation: synthesize collected data into final report

Output adheres to McKinsey/BCG consulting voice standards.

Data Authenticity Protocol

All data in the report MUST derive from provided Data Summary or External Search Findings. No hallucinations. If data is missing, state "Data not available" rather than fabricating numbers. Every major claim must be traceable to input data.

When to Use

  • User asks for market analysis, consumer insight report, financial analysis, industry research, or any consulting-grade analytical report
  • User provides a research subject and needs a structured framework
  • User provides data summaries to synthesize into a report

Phase 1: Analysis Framework Generation

Step 1.1: Identify Domain & Dimensions

DomainTypical Dimensions
Market AnalysisMarket size, growth, segmentation, drivers, competition
Brand AnalysisPositioning, share, perception, strategy
Consumer InsightsDemographics, behavior, decision journey, pain points
Financial AnalysisMacro, industry, fundamentals, metrics, valuation
Industry ResearchValue chain, market size, competition, policy, tech
Investment DDBusiness model, financials, management, opportunity, risk
Competitive IntelCompetitor ID, comparison, SWOT, positioning

Step 1.2: Select Frameworks

Select 2-4 complementary frameworks per domain:

CategoryFrameworks
StrategicSWOT, PESTEL, Porter's Five Forces, VRIO
Market & GrowthSTP, BCG Matrix, Ansoff, TAM-SAM-SOM, PLC
ConsumerDecision Journey, AARRR, RFM, JTBD
FinancialDuPont, DCF, Comparable Company, EVA
CompetitiveBenchmarking, Value Chain, Blue Ocean, Perceptual Mapping
IndustryGartner Hype Cycle, GE-McKinsey Matrix

Selection principles: domain-first, complementary not overlapping, depth over breadth, data-feasible, explicitly mapped to chapters.

Step 1.3: Chapter Skeleton

Each chapter must include:

  1. Chapter Title — professional, concise, subject-based
  2. Analysis Objective — what this chapter reveals
  3. Analysis Logic — framework or reasoning chain
  4. Core Hypothesis — to validate or refute

Step 1.4: Data Requirements Per Chapter

FieldDescription
Data MetricSpecific metric needed
Data TypeQuantitative / Qualitative / Mixed
Suggested SourcesIndustry reports, gov stats, social media, etc.
Search KeywordsQueries for data collection
PriorityP0 (Required) / P1 (Important) / P2 (Supplementary)
Time RangePeriod data should cover

Step 1.5: Visualization Plan Per Chapter

FieldDescription
Chart TypeLine, bar, pie, scatter, radar, heatmap, table
Chart TitleDescriptive title
Data MappingWhich metrics map to axes/segments
Argument Structure"What → Why → So What" narrative outline

Step 1.6: Output Framework

# [Research Subject] Analysis Framework

## Research Overview
- **Research Subject**: [...]
- **Scope**: [Geography, time range, segment]
- **Analysis Domain**: [Market / Finance / Industry / ...]
- **Core Research Questions**: [1-3 key questions]

## Framework Selection
| Chapter | Selected Framework(s) | Application |
|---------|----------------------|-------------|

## Chapter Skeleton
### 1. [Chapter Title]
- **Analysis Objective**: [...]
- **Analysis Logic**: [...]
- **Core Hypothesis**: [...]
#### Data Requirements
| # | Metric | Type | Sources | Keywords | Priority | Time |
#### Visualization & Content Plan
[Chart plan + table design + argument structure]

## Data Collection Task List
[Consolidated P0/P1 tasks for downstream data collection]

Phase 2: Report Generation

After data collection (by deep-research or other skills), synthesize into final report.

Step 2.1: Validate Inputs

Confirm Analysis Framework + Data Summary present. Flag missing P0 data.

Step 2.2: Write Report

For each sub-chapter, follow "Visual Anchor → Data Contrast → Integrated Analysis":

  1. Visual Evidence: comparison tables (charts if available)
  2. Data Contrast: Markdown table of key metrics
  3. Integrated Narrative: "What → Why → So What" (min 200 words)

Each insight must connect Data → User Psychology → Strategy Implication:

❌ Bad: "Females are 60%. Strategy: Target females."
✅ Good: "Females constitute 60% with high TGI. This suggests purchase is
   driven by aesthetic validation. Consequently, media spend should pivot
   to visual-heavy platforms."

Step 2.3: Report Structure

# [Report Title]

## Abstract
[Executive summary with key takeaways]

## 1. Introduction
[Background, objectives, methodology]

## 2. [Body Chapter]
### 2.1 [Sub-chapter]
| Metric | Brand A | Brand B |
[Integrated narrative: What → Why → So What, min 200 words]

## N+1. Conclusion
[Pure objective synthesis, NO bullet points, neutral tone]

## N+2. References
[Formatted references]

Formatting Standards

  • Tone: McKinsey/BCG — authoritative, objective, professional
  • Number formatting: English commas (1,000 not 1,000)
  • Titling: standard numbering (1., 1.1), no "Chapter/Part/Section" prefixes
  • Forbidden words: "Decoding", "DNA", "Secrets", "Unlocking"
  • No horizontal rules (---)
  • Conclusion: flowing prose, NO bullet points

Quality Checklist

Phase 1

  • Framework covers all natural dimensions for the domain
  • 2-4 complementary frameworks selected and mapped to chapters
  • Each chapter has Objective, Logic, Hypothesis
  • Data requirements specific with search keywords
  • Every chapter has a visualization plan
  • P0/P1/P2 priorities assigned

Phase 2

  • NO HALLUCINATION: all numbers traceable to Data Summary
  • All sections in order (Abstract → Intro → Body → Conclusion → References)
  • Every sub-chapter follows "Visual Anchor → Data Contrast → Analysis"
  • Every sub-chapter ends with min 200-word analytical paragraph
  • Insights follow "Data → Psychology → Strategy" chain
  • Conclusion is flowing prose, no bullets
  • Missing P0 data explicitly flagged

Output

  • Phase 1: Analysis Framework in Markdown
  • Phase 2: Final Report in Markdown, saved to .poirot/outputs/

Signals

GitHub stars
220
Forks
19
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
consulting-analysis
Source
github.com/hezaohezao/poirot