From automation-skills
Analyzes website traffic, global rank, engagement metrics, and traffic sources for any domain. Evaluates affiliate program websites, compares competitor traffic, and assesses advertiser strength.
How this skill is triggered — by the user, by Claude, or both
Slash command
/automation-skills:traffic-analyzerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Analyze website traffic, engagement, and traffic sources for any domain. Goes beyond
Analyze website traffic, engagement, and traffic sources for any domain. Goes beyond raw data — scores the domain, interprets what the traffic patterns mean for affiliate promotion, and recommends whether the program is worth your time.
A tool returns numbers. This skill returns a verdict.
Use cases:
This skill belongs to Stage S1: Research
competitor-spy identifies competitor sites — analyze their traffic sourcesdomains: string[] # (required) 1-5 domains to analyze — "heygen.com", "synthesia.io"
compare: boolean # (optional, default: true if 2+ domains) Side-by-side comparison
focus: string # (optional, default: "affiliate")
# "affiliate" — score from promoter perspective
# "competitor" — analyze as a competitor site
# "advertiser" — evaluate advertiser health
With SimilarWeb API (see shared/references/social-data-providers.md):
If social_data_config.similarweb is configured:
Without API (web_search fallback):
For each domain:
web_search "[domain] traffic similarweb" → often shows rank and visit estimates in snippetsweb_search "[domain] site traffic statistics" → third-party reportsweb_search "site:[domain]" → Google index count as proxy for content depthweb_search "[domain] alexa rank" OR "[domain] semrush traffic" → alternative sourcesweb_fetch "https://www.similarweb.com/website/[domain]/" → extract visible data from SimilarWeb free page (may be limited)Note: web_search data is approximate. SimilarWeb API provides exact metrics.
For each domain, analyze and interpret:
Traffic Volume:
global_rank: number # Lower = better. <10K = major site, <100K = solid, <1M = niche
country_rank: number # Rank in primary country
monthly_visits: string # "1.2M", "350K", "45K"
visits_trend: string # "growing" | "stable" | "declining" (if historical data available)
Engagement Quality:
pages_per_visit: number # >3 = good engagement, <2 = bouncy
avg_visit_duration: string # ">3 min" = engaged, "<1 min" = low quality
bounce_rate: number # <40% = excellent, 40-60% = normal, >60% = concerning
Traffic Sources Breakdown:
direct: number # % — brand strength indicator
search: number # % — SEO strength
social: number # % — social media presence
referral: number # % — partnership/affiliate ecosystem
paid: number # % — ad spend (high paid = advertiser invests in acquisition)
For affiliate promoters (focus: "affiliate"):
Score the domain as an affiliate promotion target:
| Signal | Good (8-10) | OK (5-7) | Red Flag (1-4) |
|---|---|---|---|
| Monthly visits | >500K | 50K-500K | <50K |
| Bounce rate | <40% | 40-60% | >70% |
| Search traffic | >30% | 15-30% | <10% (overly dependent on ads) |
| Brand (direct) | >30% | 15-30% | <10% (nobody knows them) |
| Pages/visit | >4 | 2-4 | <2 |
Why this matters for affiliates:
For competitor analysis (focus: "competitor"):
For advertiser evaluation (focus: "advertiser"):
Calculate an overall Traffic Health Score (0-100):
traffic_score = (
rank_score × 0.20 + # Based on global rank
volume_score × 0.25 + # Based on monthly visits
engagement_score × 0.25 + # Based on bounce rate + pages/visit + duration
diversity_score × 0.15 + # Traffic source diversity (not overly dependent on one channel)
brand_score × 0.15 # Direct traffic % (brand recognition)
)
Score interpretation:
If 2+ domains provided, create side-by-side comparison:
Before presenting output, verify:
If any check fails, fix before delivering. Do not flag checklist to user.
output_schema_version: "1.0.0"
domains_analyzed:
- domain: string
data_source: "similarweb_api" | "web_search_estimate"
metrics:
global_rank: number | null
country_rank: number | null
country: string | null
monthly_visits: string
pages_per_visit: number | null
avg_duration: string | null
bounce_rate: number | null
traffic_sources:
direct: number | null # percentage
search: number | null
social: number | null
referral: number | null
paid: number | null
traffic_score: number # 0-100
verdict: string # "excellent" | "good" | "fair" | "weak" | "red_flag"
interpretation: string # 2-3 sentence analysis based on focus
comparison: object | null # if 2+ domains
winner: string
reasoning: string
recommended_next_skill: string
## Traffic Analysis: [Domain(s)]
### Data Source
📊 **[SimilarWeb API | Web search estimates (approximate)]**
---
### [domain1.com] — Traffic Score: [XX]/100 — [Verdict]
| Metric | Value | Assessment |
|--------|-------|------------|
| Global Rank | #XX,XXX | [Good/Fair/Low] |
| Monthly Visits | X.XM | [High/Medium/Low] |
| Pages/Visit | X.X | [Engaged/Average/Bouncy] |
| Avg Duration | Xm Xs | [Good/Low] |
| Bounce Rate | XX% | [Healthy/Concerning/High] |
**Traffic Sources:**
Direct: ██████████░░░░░░ 35% (strong brand) Search: ████████░░░░░░░░ 28% (good SEO) Social: ████░░░░░░░░░░░░ 15% (social presence) Referral: ███░░░░░░░░░░░░░ 12% (affiliate ecosystem) Paid: ██░░░░░░░░░░░░░░ 10% (moderate ad spend)
**What This Means for You:**
[2-3 sentences interpreting metrics for the user's focus — affiliate/competitor/advertiser]
---
### [If comparing 2+ domains]
### Head-to-Head: [domain1] vs [domain2]
| Metric | [domain1] | [domain2] | Winner |
|--------|-----------|-----------|--------|
| Traffic Score | XX/100 | XX/100 | [domain] |
| Monthly Visits | X.XM | XXK | [domain] |
| Engagement | X.X pg/visit | X.X pg/visit | [domain] |
| Brand Strength | XX% direct | XX% direct | [domain] |
| SEO | XX% search | XX% search | [domain] |
**Verdict:** [domain1] is the stronger affiliate promotion target because [reasoning].
---
### 🎯 Recommendation
[Specific, actionable recommendation based on focus]
### Next Steps
- `affiliate-program-search` — check commission details for [domain]
- `competitor-spy` — deep dive into their affiliate strategy
- `trending-content-scout` — find what content about [domain/product] is performing
shared/references/social-data-providers.md." Still provide estimated score.Example 1:
User: "Is HeyGen worth promoting? Check their traffic."
→ domain: "heygen.com", focus: "affiliate"
→ SimilarWeb or web_search → Global rank: ~15K, 2.1M monthly visits
→ Score: 82/100 — "Excellent. HeyGen has strong traffic with healthy engagement. 35% direct traffic shows strong brand recognition. Your referral links benefit from existing brand awareness."
→ Next: affiliate-program-search for HeyGen commission details
Example 2: User: "Compare Notion vs ClickUp vs Monday.com traffic for my productivity niche" → domains: ["notion.so", "clickup.com", "monday.com"] → Analyze all 3, side-by-side comparison → Winner: Notion (highest traffic, best engagement) → But: ClickUp has highest referral % (12%) = strongest affiliate ecosystem → may convert better
Example 3: User: "I found this small SaaS tool — screenpal.com. Is the advertiser legit?" → domain: "screenpal.com", focus: "advertiser" → Global rank: ~180K, ~300K monthly visits → Score: 55/100 — "Fair. Niche tool with moderate traffic. Growing steadily. Low paid traffic (2%) suggests bootstrapped. Engagement is good (3.8 pages/visit). Worth promoting if commission is strong, but don't expect brand-name conversion rates."
When this skill produces unexpected, incomplete, or incorrect output, generate a
skill_feedback block (see shared/references/feedback-protocol.md for full schema).
Skill-specific failure modes:
data_quality, note domain.data_quality, severity: medium.wrong_output.Auto-detect triggers:
traffic_score is 0 or null for a well-known domaintraffic_sources percentages are nullReport issues: GitHub Issues | Discussions
shared/references/social-data-providers.md — SimilarWeb API configurationshared/references/flywheel-connections.md — master flywheel connection mapshared/references/affiliate-glossary.md — affiliate marketing terminologyshared/references/feedback-protocol.md — issue detection and reporting standardaffiliate-program-search (S1) — traffic score as program evaluation factorcompetitor-spy (S1) — traffic sources reveal competitor strategyniche-opportunity-finder (S1) — traffic data validates niche demandcontent-angle-ranker (S1) — traffic source breakdown informs platform prioritizationtrending-content-scout (S1) — social traffic % hints at which platforms to scoutcompetitor-spy (S1) — competitor domains to analyzeaffiliate-program-search (S1) — program URLs to evaluateniche-opportunity-finder (S1) — top program domains in a nicheperformance-report shows your referral contribution to the advertiser → compare your traffic impact over time → prioritize programs where you move the needlechain_metadata:
skill_slug: "traffic-analyzer"
stage: "research"
timestamp: string
suggested_next:
- "affiliate-program-search"
- "competitor-spy"
- "trending-content-scout"
npx claudepluginhub affitor/affiliate-skills --plugin research-skillsAnalyzes a single URL's SEO performance: rankings, traffic, position history, SERP context, and AI Search citation status. Produces a keep/refresh/consolidate/kill verdict.
Fetches live SEO data via the DataForSEO MCP server: SERP results, keyword metrics, backlinks, on-page analysis, and AI visibility (ChatGPT/LLM mentions). Includes cost management guardrails.
Provides live SEO data via DataForSEO: SERP results, keyword metrics, backlinks, on-page analysis, competitor data, and AI visibility tracking. Useful for real-time search data and SEO analysis.