KS
Killer-Skills

market-research — market-research MCP skill market-research MCP skill, how to use market-research for TAM analysis, market-research vs traditional research, install market-research for Claude, market-research competitive analysis, what is market-research AI agent, market-research setup guide, investor due diligence AI skill, Anthropic Claude market research

Verified
v1.0.0
GitHub

About this Skill

Essential for Business Intelligence Agents conducting data-driven market analysis with source attribution. market-research is an AI Agent skill for MCP servers that conducts market sizing, competitor comparisons, and investor due diligence. It produces decision-oriented summaries with source attribution, adhering to standards that prioritize recent data and call out stale information.

Features

Generates TAM/SAM/SOM market sizing estimates for business planning
Performs competitive analysis and adjacent product comparisons
Builds investor dossiers for outreach preparation
Pressure-tests business theses before market entry
Attributes every important claim to a verifiable source
Flags stale data and prioritizes recent information in reports

# Core Topics

affaan-m affaan-m
[62.0k]
[7678]
Updated: 3/6/2026

Quality Score

Top 5%
76
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add affaan-m/everything-claude-code/market-research

Agent Capability Analysis

The market-research MCP Server by affaan-m is an open-source Categories.official integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for market-research MCP skill, how to use market-research for TAM analysis, market-research vs traditional research.

Ideal Agent Persona

Essential for Business Intelligence Agents conducting data-driven market analysis with source attribution.

Core Value

Conducts comprehensive market research, competitive analysis, and investor due diligence with rigorous source attribution. Delivers decision-oriented summaries for TAM/SAM/SOM estimates, technology scans, and investor dossiers.

Capabilities Granted for market-research MCP Server

Building market sizing estimates (TAM/SAM/SOM)
Performing competitive analysis with source attribution
Preparing investor due diligence reports
Pressure-testing business theses with recent data

! Prerequisites & Limits

  • Requires access to current market data sources
  • Depends on availability of recent public data
  • Limited to publicly available information
Project
SKILL.md
1.8 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8
SKILL.md
Readonly

Market Research

Produce research that supports decisions, not research theater.

When to Activate

  • researching a market, category, company, investor, or technology trend
  • building TAM/SAM/SOM estimates
  • comparing competitors or adjacent products
  • preparing investor dossiers before outreach
  • pressure-testing a thesis before building, funding, or entering a market

Research Standards

  1. Every important claim needs a source.
  2. Prefer recent data and call out stale data.
  3. Include contrarian evidence and downside cases.
  4. Translate findings into a decision, not just a summary.
  5. Separate fact, inference, and recommendation clearly.

Common Research Modes

Investor / Fund Diligence

Collect:

  • fund size, stage, and typical check size
  • relevant portfolio companies
  • public thesis and recent activity
  • reasons the fund is or is not a fit
  • any obvious red flags or mismatches

Competitive Analysis

Collect:

  • product reality, not marketing copy
  • funding and investor history if public
  • traction metrics if public
  • distribution and pricing clues
  • strengths, weaknesses, and positioning gaps

Market Sizing

Use:

  • top-down estimates from reports or public datasets
  • bottom-up sanity checks from realistic customer acquisition assumptions
  • explicit assumptions for every leap in logic

Technology / Vendor Research

Collect:

  • how it works
  • trade-offs and adoption signals
  • integration complexity
  • lock-in, security, compliance, and operational risk

Output Format

Default structure:

  1. executive summary
  2. key findings
  3. implications
  4. risks and caveats
  5. recommendation
  6. sources

Quality Gate

Before delivering:

  • all numbers are sourced or labeled as estimates
  • old data is flagged
  • the recommendation follows from the evidence
  • risks and counterarguments are included
  • the output makes a decision easier

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