product-team/skills/competitive-teardown/SKILL.md
Analyzes competitor products and companies by synthesizing data from pricing pages, app store reviews, job postings, SEO signals, and social media into structured competitive intelligence. Produces feature comparison matrices scored across 12 dimensions, SWOT analyses, positioning maps, UX audits, pricing model breakdowns, action item roadmaps, and stakeholder presentation templates. Use when conducting competitor analysis, comparing products against competitors, researching the competitive landscape, building battle cards for sales, preparing for a product strategy or roadmap session, responding to a competitor's new feature or pricing change, or performing a quarterly competitive review.
npx skillsauth add alirezarezvani/claude-skills competitive-teardownInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Tier: POWERFUL
Category: Product Team
Domain: Competitive Intelligence, Product Strategy, Market Analysis
Follow these steps in sequence to produce a complete teardown:
references/data-collection-guide.md to gather raw signals from at least 3 sources per competitor (website, reviews, job postings, SEO, social).references/analysis-templates.md (Feature Matrix, Pricing Analysis, SWOT, Positioning Map, UX Audit).Full executable scripts for each source are in
references/data-collection-guide.md. Summaries of what to capture are below.
Key things to capture:
Review sentiment categories:
Sample App Store query (iTunes Search API):
GET https://itunes.apple.com/search?term=<competitor_name>&entity=software&limit=1
# Extract trackId, then:
GET https://itunes.apple.com/rss/customerreviews/id=<trackId>/sortBy=mostRecent/json?l=en&limit=50
Parse entry[].content.label for review text and entry[].im:rating.label for star rating.
Signals from job postings:
SEO signals to capture:
Capture recent mentions via Twitter/X API v2, Reddit, or LinkedIn. Look for recurring praise, complaints, and feature requests. See references/data-collection-guide.md for API query examples.
| # | Dimension | 1 (Weak) | 3 (Average) | 5 (Best-in-class) | |---|-----------|----------|-------------|-------------------| | 1 | Features | Core only, many gaps | Solid coverage | Comprehensive + unique | | 2 | Pricing | Confusing / overpriced | Market-rate, clear | Transparent, flexible, fair | | 3 | UX | Confusing, high friction | Functional | Delightful, minimal friction | | 4 | Performance | Slow, unreliable | Acceptable | Fast, high uptime | | 5 | Docs | Sparse, outdated | Decent coverage | Comprehensive, searchable | | 6 | Support | Email only, slow | Chat + email | 24/7, great response | | 7 | Integrations | 0-5 integrations | 6-25 | 26+ or deep ecosystem | | 8 | Security | No mentions | SOC2 claimed | SOC2 Type II, ISO 27001 | | 9 | Scalability | No enterprise tier | Mid-market ready | Enterprise-grade | | 10 | Brand | Generic, unmemorable | Decent positioning | Strong, differentiated | | 11 | Community | None | Forum / Slack | Active, vibrant community | | 12 | Innovation | No recent releases | Quarterly | Frequent, meaningful |
Example completed row (Competitor: Acme Corp, Dimension 3 – UX):
| Dimension | Acme Corp Score | Evidence | |-----------|----------------|---------| | UX | 2 | App Store reviews cite "confusing navigation" (38 mentions); onboarding requires 7 steps before TTFV; no onboarding wizard; CC required at signup. |
Apply this pattern to all 12 dimensions for each competitor.
Full template markdown is in
references/analysis-templates.md. Abbreviated reference below.
Rows: core features, pricing tiers, platform capabilities (web, iOS, Android, API).
Columns: your product + up to 3 competitors.
Score each cell 1–5. Sum to get total out of 60.
Score legend: 5=Best-in-class, 4=Strong, 3=Average, 2=Below average, 1=Weak/Missing
Capture per competitor: model type (per-seat / usage-based / flat rate / freemium), entry/mid/enterprise price points, free trial length.
Summarize: price leader, value leader, premium positioning, your position, and 2–3 pricing opportunity bullets.
For each competitor: 3–5 bullets per quadrant (Strengths, Weaknesses, Opportunities for us, Threats to us). Anchor every bullet to a data signal (review quote, job posting count, pricing page, etc.).
2x2 axes (e.g., Simple ↔ Complex / Low Value ↔ High Value). Place each competitor and your product. Bubble size = market share or funding. See references/analysis-templates.md for ASCII and editable versions.
Onboarding: TTFV (minutes), steps to activation, CC-required, onboarding wizard quality.
Key workflows: steps, friction points, comparative score (yours vs. theirs).
Mobile: iOS/Android ratings, feature parity, top complaint and praise.
Navigation: global search, keyboard shortcuts, in-app help.
| Horizon | Effort | Examples | |---------|--------|---------| | Quick wins (0–4 wks) | Low | Add review badges, publish comparison landing page | | Medium-term (1–3 mo) | Moderate | Launch free tier, improve onboarding TTFV, add top-requested integration | | Strategic (3–12 mo) | High | Enter new market, build API v2, achieve SOC2 Type II |
product-team/product-strategist/) — Competitive insights feed OKR and strategy planningproduct-team/landing-page-generator/) — Competitive positioning informs landing page messagingdata-ai
Use when you want to understand what Claude contributed vs what you drove in a session. Triggers on: /collab-proof, session retrospective, ai contribution analysis, collaboration evidence, what did claude do.
data-ai
Personal coach that teaches users to become Claude power users. Use this skill the FIRST time a user asks to "learn Claude", "be a power user", "coach me", "teach me Claude tricks", "what can Claude do", "make me better at prompting", or any variation. After activation, also use it on EVERY subsequent turn to detect missed optimization opportunities (vague prompts, ignored capabilities, manual work Claude could automate) and surface a single power-user tip. Trigger generously — most users do not know what they do not know, so err on the side of coaching.
development
Use when designing or revisiting product pricing — selecting a pricing model (subscription seat-based, usage-based, value-based, freemium, or hybrid), running Van Westendorp Price Sensitivity Meter analysis on WTP survey data, or designing Good/Better/Best packaging tiers. Recommends a model and a price range with trade-offs, never a single number. For Commercial leads, Product Marketing, and CMOs at the pricing-design moment — not deal-by-deal discounting, not brand positioning.
testing
Use when a startup is approached by a prospective partner and someone has to decide should we sign this partner, at what partner tier (referral / reseller / OEM / SI-consulting / strategic alliance), with what joint GTM commitment, and at what revshare. Classifies partner tier from independent-demand evidence vs. preferential-terms hunting, designs a 90-day joint GTM plan, models revshare against direct-sale margin, and surfaces kill criteria for unwinding under-performing partnerships. For Head of Partnerships, Head of BD, and Founder-CEOs doing reseller agreement, OEM deal, or strategic alliance review — not technical sale enablement, not channel cost economics, not M&A.