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Research

Skill donatassimkus/claude-ai-skills/skills/research

Growth marketing skills for Claude Code, Cursor, and any AI agent: SEO, CRM, marketing automation, inbox triage, and pre-launch QA. Paste one prompt and your agent installs the method, then applies it to your own accounts.

Install
npx -y skills add donatassimkus/claude-ai-skills --skill research

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 14 days oldThe repository was created 14 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Market research, competitor analysis, audience research, trend analysis, product research, pricing research. Invoke when: sizing a market, mapping competitors, building an ICP, analyzing industry trends, doing pricing research, mystery shopping a competitor, building a competitive intelligence report, or finding out what an audience actually wants before building or spending. Product-specific user research and feature decisions are an adjacent discipline handled separately.

SKILL.md

3.6 KB, as published. Nobody here has run it

Research Skill

Research with a bias toward actionable findings. No academic reports. Every output should answer: so what do I do with this?

Project context is loaded from the active CLAUDE.md. Frame all research findings in terms of that project's goals and competitive position.

When invoked

$ARGUMENTS defines the research type and subject. If unclear, ask one question to clarify scope before proceeding.

Research types

Competitor analysis

For each competitor:

  1. Product: what they offer, pricing tiers, positioning, differentiators
  2. Acquisition: how they get customers (SEO, paid, social, partnerships, viral)
  3. Retention: what keeps customers (features, community, lock-in)
  4. Weaknesses: what they do badly, where reviews complain, what they are missing
  5. Opportunity: where they are vulnerable and you can win

Output: comparison table + "where to attack" summary.

Market research

  1. Market size and growth direction
  2. Key segments and who is underserved
  3. Buying triggers: what causes someone to buy in this category?
  4. Objections: what stops people from buying?
  5. Pricing norms: what does the market expect to pay?
  6. Distribution channels that work in this market

Output: market snapshot + top 3 opportunities.

Audience research

  1. Who they are: demographics, job, situation
  2. Pain: what problem are they trying to solve right now?
  3. Language: how do they describe the problem in their own words?
  4. Watering holes: where do they hang out online?
  5. Buying behavior: how do they evaluate and decide?
  6. Triggers: what causes them to act now vs later?

Output: audience profile + messaging implications.

Pricing research

  1. Competitor pricing tiers and what each tier includes
  2. Where the market anchors value
  3. Price sensitivity signals (free trial vs freemium vs demo)
  4. Packaging patterns (per seat, per usage, flat, tiered)
  5. Upsell and expansion revenue patterns

Output: pricing benchmark + recommended positioning.

Keyword / SEO research

Full SEO research is a separate discipline; hand it off there rather than half-running it here. This section covers only:

  • Quick competitive keyword gap analysis
  • Identifying what competitors rank for that you do not
  • Finding uncontested long-tail opportunities

Output format

Standard structure:

  1. Key findings (3-7 bullets, most important first)
  2. Evidence or source for each finding
  3. Implications: what this means for the project
  4. Recommended action: one or two concrete next steps

Rules:

  • Label assumptions clearly.
  • Do not invent facts. If data is not available, say so and proceed with labeled estimates.
  • Prioritize findings by revenue or strategic impact.
  • No padding. If there are only 3 meaningful findings, deliver 3.

Adjacent disciplines (where this skill stops)

  • Product decisions informed by market research: product-market fit, roadmap, feature prioritization.
  • Market sizing feeding investor narratives and pitch decks.
  • Full SEO and keyword research, beyond the quick competitive gap analysis above.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.