Spartan-ai-toolkit market-research

Run market research, competitive analysis, investor due diligence, and industry scans. Use when the user wants market sizing, competitor comparisons, fund research, or tech scans.

install
source · Clone the upstream repo
git clone https://github.com/c0x12c/ai-toolkit
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/c0x12c/ai-toolkit "$T" && mkdir -p ~/.claude/skills && cp -r "$T/toolkit/skills/market-research" ~/.claude/skills/spartan-stratos-spartan-ai-toolkit-market-research-b128a3 && rm -rf "$T"
manifest: toolkit/skills/market-research/SKILL.md
source content

Market Research

Make research that helps decisions, not research for show.

When to Use

  • Researching a market, company, investor, or tech trend
  • Building TAM/SAM/SOM numbers
  • Comparing competitors
  • Checking investor fit before outreach
  • Testing a thesis before building

Process

1. Pick the Research Type

Figure out which kind of research the user needs:

  • Investor / Fund Check
  • Competitor Check
  • Market Size
  • Tech / Tool Research

2. Run Investor / Fund Check

Get:

  • Fund size, stage, check size
  • Portfolio companies that matter
  • Public thesis and recent deals
  • Why they fit or don't fit
  • Red flags

3. Run Competitor Check

Get:

  • What the product really does (not marketing fluff)
  • Funding and investors
  • Traction if public
  • How they get users and what they charge
  • Strengths, weaknesses, gaps

4. Run Market Size

Use:

  • Top-down from reports
  • Bottom-up from real customer numbers
  • Show your math. Every guess should be clear.

5. Run Tech / Tool Research

Get:

  • How it works
  • Trade-offs and who's using it
  • How hard to set up
  • Lock-in, security, and risk

6. Write It Up

Structure every deliverable as:

  1. Quick summary (2-3 sentences)
  2. Key findings
  3. What this means
  4. Risks and caveats
  5. What to do next
  6. Sources

Rules

  • Every big claim needs a source.
  • Use recent data. Flag old data.
  • Include the bad news too. Show risks.
  • End with a decision, not just a summary.
  • Keep facts, guesses, and suggestions separate.
  • All numbers have sources or are marked as guesses.
  • Old data is flagged.
  • The suggestion follows from the facts.
  • Someone can make a decision from this.

Gotchas

  • Top-down TAM is lazy and always wrong. "10% of the $X billion market" is not analysis. Bottom-up from real customer numbers or go home.
  • Analyst reports have built-in bias. Reports from vendors (like AWS sizing the cloud market) overstate their own segment. Use independent sources.
  • Revenue proxies are unreliable. SimilarWeb traffic estimates can be off by 5x. Combine multiple signals: hiring, social, Crunchbase, app store rankings.
  • Don't confuse market size with addressable market. The CRM market is $80B, but if you're building for freelancers, your market is a fraction of that.
  • Recency matters. A market growing 40% in 2024 might be flat in 2026. Always check the latest data points, not just the headline number.

Output

Save to the project's

02-research/
folder.

Format each deliverable with: quick summary, key findings, what this means, risks and caveats, next steps, and sources.