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affaan-m/market-research

affaan-m

market-research

Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.

global
0installs0uses~543
v1.1Saved Apr 20, 2026

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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Overall Score

82/100

Grade

B

Good

Safety

95

Quality

78

Clarity

84

Completeness

75

Summary

A market research guidance skill that directs agents to conduct sourced, decision-oriented research on markets, competitors, investors, and technologies. The skill emphasizes attribution, contrarian evidence, and clear separation of fact from inference—designed to support business decisions rather than generate unfocused analysis.

Detected Capabilities

research planning and structuresource attribution and validationcompetitive intelligence gatheringmarket sizing estimation (top-down and bottom-up)investor due diligencerisk and caveat identificationdecision-oriented synthesis

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

market sizingcompetitive analysisinvestor researchdue diligencetechnology evaluationmarket entryvendor assessment

Use Cases

  • evaluate market size and opportunity (TAM/SAM/SOM)
  • prepare competitive analysis before entering a market
  • research investor funds and assess fit before outreach
  • technology vendor evaluation for integration decisions
  • pressure-test business thesis with contradictory evidence

Quality Notes

  • Skill provides clear activation criteria tied to real business use cases—user intent is unambiguous.
  • Research standards are well-defined and enforce rigor: attribution, recency checks, contrarian evidence, and fact/inference/recommendation separation reduce speculation.
  • Output format is prescriptive and actionable—agent knows exactly what structure to produce.
  • Quality gate at the end ensures outputs meet professional standards before delivery.
  • Skill emphasizes decision-orientation, which makes research actionable rather than theoretical.
  • No execution code or external tools required—this is a guidance/methodology skill, not a tool orchestrator.
  • Coverage of multiple research domains (investors, competitors, markets, vendors) within unified framework.
  • Could benefit from explicit examples of source hierarchy (primary vs. secondary sources, gray literature) and how to handle data gaps.
  • No mention of research ethics, bias detection, or how to handle proprietary vs. public information—minor gap for due diligence contexts.
  • Skill does not define what 'recent' means (e.g., 6 months, 1 year) or how to flag stale data quantitatively.
Model: claude-haiku-4-5-20251001Analyzed: Apr 20, 2026

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Version History

v1.1

Content updated

2026-04-20

Latest
v1.0

Seeded from github.com/affaan-m/everything-claude-code

2026-03-16

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