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Get Started Free →When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files.
.claude/skills/mkurman-competitor-profiling/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 217% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 216% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 107% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 94% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 79% | 0% |
Before synthesizing the profile, persist all raw scrape, SEO, and review data to disk so it can be re-read, audited, or re-used later without re-running expensive API calls.
Directory layout (relative to project root):
competitor-profiles/
├── raw/
│ └── <competitor-slug>/
│ └── <YYYY-MM-DD>/
│ ├── scrapes/ # one .md file per scraped page (homepage.md, pricing.md, ...)
│ ├── seo/ # one .json file per DataForSEO call (backlinks-summary.json, ranked-keywords.json, ...)
│ └── reviews/ # one .md or .json file per review source (g2.md, capterra.md, ...)
├── <competitor-slug>.md # final synthesized profile
└── _summary.md # cross-competitor summaryRules:
<competitor-slug> is lowercase, hyphenated (e.g. responsehub, safe-base)<YYYY-MM-DD> is the date the data was pulled — supports re-running and diffing snapshots over timescrapes/<page-name>.mdseo/<endpoint-name>.jsonreviews/<source>.md (cleaned text) or .json (raw)The synthesized profile (<competitor-slug>.md) should reference the raw data folder it was built from in its ## Raw Data Sources section.
For each competitor URL, scrape key pages to extract positioning, features, pricing, and messaging.
Use Firecrawl Map to discover the competitor's site structure and identify key pages:
firecrawl_map → competitor URLFrom the map, identify and prioritize these page types:
Use Firecrawl Scrape on each identified page:
firecrawl_scrape → each key page URLSave each result to competitor-profiles/raw/<competitor-slug>/<YYYY-MM-DD>/scrapes/<page-name>.md before extracting fields.
Extract from each page:
| Page | What to Extract | |------|----------------| | Homepage | Headline, subheadline, value proposition, primary CTA, social proof claims, target audience signals | | Pricing | Tiers, prices, feature breakdown per tier, billing options, free tier/trial details, enterprise pricing signals | | Features | Feature categories, key capabilities, how they describe each feature, screenshots/demo signals | | About | Founding story, team size, funding, mission statement, headquarters | | Customers | Named customers, logos, industries served, case study themes | | Integrations | Integration count, key integrations, categories | | Changelog | Release velocity, recent focus areas, product direction signals |
Use Firecrawl Scrape or Firecrawl Search to find:
Save each scraped review page to competitor-profiles/raw/<competitor-slug>/<YYYY-MM-DD>/reviews/<source>.md. Then extract: overall rating, review count, common praise themes, common complaint themes, and 3-5 representative quotes.
Use DataForSEO MCP tools to gather quantitative competitive intelligence. Save each raw response as JSON to competitor-profiles/raw/<competitor-slug>/<YYYY-MM-DD>/seo/<endpoint-name>.json before parsing it into the profile. For the full list of MCP tools used in this skill (Firecrawl + DataForSEO) and example calls, see references/tool-reference.md.
Use backlinks_summary to get:
Use backlinks_referring_domains for:
Use dataforseo_labs_google_ranked_keywords to get:
Use dataforseo_labs_google_domain_rank_overview for:
Use dataforseo_labs_google_keywords_for_site to discover:
Use dataforseo_labs_google_competitors_domain to find:
Use dataforseo_labs_google_relevant_pages to find:
Combine scraped content with SEO data to build the profile. Cross-reference claims (e.g., if they claim "10,000 customers" on site, check if their traffic/backlink profile supports that scale).
Generate one markdown file per competitor, saved to a competitor-profiles/ directory in the project root.
Filename: competitor-profiles/[competitor-name].md
For the full profile and summary templates: See references/templates.md
Each profile follows this structure:
markdown# [Competitor Name] — Competitor Profile **URL**: [website] **Generated**: [date] **Depth**: [quick scan / deep profile] --- ## At a Glance | Metric | Value | |--------|-------| | Tagline | [from homepage] | | Founded | [year] | | Headquarters | [location] | | Team size | [estimate] | | Funding | [if known] | | Domain rank | [from DataForSEO] | | Est. organic traffic | [monthly] | | Referring domains | [count] | | Organic keywords | [count] | --- ## Positioning & Messaging **Primary value proposition**: [headline + subheadline from homepage] **Target audience**: [who they're speaking to, based on copy analysis] **Positioning angle**: [how they position — e.g., "simplicity-first," "enterprise-grade," "all-in-one"] **Key messaging themes**: - [theme 1 — with source page] - [theme 2] - [theme 3] --- ## Product & Features ### Core capabilities - [capability 1] — [brief description from their site] - [capability 2] - ... ### Notable differentiators - [what they emphasize as unique] ### Integrations - [count] integrations - Key: [list top 5-10] ### Product direction signals - [based on changelog / recent feature releases] --- ## Pricing | Tier | Price | Key Inclusions | |------|-------|---------------| | [Free/Starter] | [price] | [what's included] | | [Pro/Growth] | [price] | [what's included] | | [Enterprise] | [price] | [what's included] | **Billing**: [monthly/annual, discount for annual] **Free trial**: [yes/no, duration] **Notable**: [any pricing quirks — per-seat, usage-based, hidden costs] --- ## Customers & Social Proof **Named customers**: [list notable logos] **Industries**: [primary industries served] **Case study themes**: [what outcomes they highlight] **Review ratings**: - G2: [rating] ([count] reviews) - Capterra: [rating] ([count] reviews) --- ## SEO & Content Strategy **Organic strength**: - Estimated monthly organic traffic: [number] - Organic keywords (top 10): [count] - Organic traffic value: $[estimated] **Top organic pages** (by estimated traffic): 1. [page URL] — [keyword] — [est. traffic] 2. [page URL] — [keyword] — [est. traffic] 3. [page URL] — [keyword] — [est. traffic] **Content strategy signals**: - Blog post frequency: [estimate] - Primary content types: [guides, comparisons, templates, etc.] - Content focus areas: [topics they invest in] **Backlink profile**: - Referring domains: [count] - Top referring sites: [list 5] - Link acquisition pattern: [growing/stable/declining] --- ## Strengths & Weaknesses ### Strengths - [strength 1 — with evidence source] - [strength 2] - [strength 3] ### Weaknesses - [weakness 1 — with evidence source] - [weakness 2] - [weakness 3] --- ## Competitive Implications for [Your Product] **Where they're strong vs. us**: [areas where this competitor has an advantage] **Where we're strong vs. them**: [areas where you have an advantage] **Opportunities**: [gaps in their offering or positioning we can exploit] **Threats**: [areas where they're improving or gaining ground] --- ## Raw Data Sources - Homepage scraped: [date] - Pricing page scraped: [date] - SEO data pulled: [date] - Review data pulled: [date, sources]
After profiling all competitors, generate a competitor-profiles/_summary.md that includes:
Default to quick scan unless the user requests deep profiling or specifies a small number of competitors (3 or fewer).
When profiling more than one competitor:
Profiles are snapshots. When updating:
## Change Log section at the bottomOnly ask if not answered by context or input:
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 38,209 | 7,640 | -80% | 1 | 1 | 0% | 5,132 | 4,070 | -21% | 0 | 0 | — |
case-02 | fail→fail | 31,007 | 13,285 | -57% | 1 | 1 | 0% | 4,919 | 4,029 | -18% | 0 | 0 | — |
case-03 | fail→fail | 36,817 | 12,052 | -67% | 1 | 1 | 0% | 6,036 | 4,157 | -31% | 0 | 0 | — |
case-04 | pass→pass | 23,061 | 30,478 | +32% | 1 | 1 | 0% | 3,812 | 8,438 | +121% | 0 | 0 | — |
case-05 | pass→pass | 14,406 | 15,861 | +10% | 1 | 1 | 0% | 2,049 | 5,154 | +152% | 0 | 0 | — |
case-06 | pass→pass | 26,770 | 19,927 | -26% | 1 | 1 | 0% | 2,393 | 5,906 | +147% | 0 | 0 | — |
case-07 | fail→pass | 7,594 | 2,930 | -61% | 1 | 1 | 0% | 1,069 | 3,393 | +217% | 0 | 0 | — |
case-08 | fail→fail | 16,035 | 35,971 | +124% | 1 | 1 | 0% | 2,340 | 9,132 | +290% | 0 | 0 | — |
case-09 | fail→pass | 28,829 | 3,987 | -86% | 1 | 1 | 0% | 1,067 | 3,375 | +216% | 0 | 0 | — |
case-10 | fail→pass | 51,273 | 3,148 | -94% | 1 | 1 | 0% | 1,738 | 3,589 | +107% | 0 | 0 | — |
case-11 | pass→pass | 11,211 | 6,415 | -43% | 1 | 1 | 0% | 1,917 | 4,019 | +110% | 0 | 0 | — |
case-12 | pass→pass | 9,353 | 4,478 | -52% | 1 | 1 | 0% | 1,509 | 3,743 | +148% | 0 | 0 | — |
case-13 | fail→fail | 8,985 | 3,590 | -60% | 1 | 1 | 0% | 1,308 | 3,359 | +157% | 0 | 0 | — |
case-14 | fail→fail | 8,588 | 3,155 | -63% | 1 | 1 | 0% | 1,381 | 3,461 | +151% | 0 | 0 | — |
case-15 | pass→fail | 13,542 | 11,595 | -14% | 1 | 1 | 0% | 2,145 | 3,782 | +76% | 0 | 0 | — |
case-16 | fail→pass | 10,423 | 2,237 | -79% | 1 | 1 | 0% | 1,686 | 3,267 | +94% | 0 | 0 | — |
case-17 | fail→pass | 12,549 | 2,964 | -76% | 1 | 1 | 0% | 1,940 | 3,478 | +79% | 0 | 0 | — |
case-18 | fail→fail | 8,972 | 6,094 | -32% | 1 | 1 | 0% | 1,301 | 3,511 | +170% | 0 | 0 | — |
case-19 | pass→pass | 7,700 | 2,098 | -73% | 1 | 1 | 0% | 1,108 | 3,184 | +187% | 0 | 0 | — |
case-20 | fail→fail | 6,434 | 2,444 | -62% | 1 | 1 | 0% | 944 | 3,258 | +245% | 0 | 0 | — |
case-21 | fail→pass | 18,321 | 16,611 | -9% | 1 | 1 | 0% | 2,673 | 5,368 | +101% | 0 | 0 | — |
case-22 | fail→pass | 12,745 | 9,155 | -28% | 1 | 1 | 0% | 1,917 | 4,333 | +126% | 0 | 0 | — |
case-23 | fail→pass | 15,962 | 8,252 | -48% | 1 | 1 | 0% | 2,313 | 4,209 | +82% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted, and 19 counted toward the lift figure. The other 4 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +30 percentage points is the difference between those two pass rates over the 19 comparable cases. 2 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.