Agent skill

Traffic Analyzer

by Affitor in Affitor/affiliate-skills

Analyze website traffic, global rank, engagement metrics, and traffic sources for any domain.

MITAuto-check passedMarketing & SEO

Install Traffic Analyzer

skills CLI
$ npx skills add Affitor/affiliate-skills --skill traffic-analyzer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Affitor/affiliate-skills traffic-analyzer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Affitor/affiliate-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/traffic-analyzer .claude/skills/traffic-analyzer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
traffic-analyzer
GitHub stars
698
Token cost
~3.7k tokens
SKILL.md length
1,136 words
Files
1
Skills in repo
50
Repo updated
First seen
Licence
MIT

At a glance

Analyze website traffic, global rank, engagement metrics, and traffic sources for any domain.

  • Works in 6 steps: Gather Traffic Data → Analyze Core Metrics → Interpret for Use Case → …
  • Evaluate affiliate program websites
  • SKILL.md covers Stage, When to Use, Input Schema and Workflow, plus 7 more sections
  • Reaches similarweb.com

What it does

Traffic Analyzer is an agent skill from Affitor/affiliate-skills. Analyze website traffic, global rank, engagement metrics, and traffic sources for any domain. Use this skill to evaluate affiliate program websites, compare competitor traffic, assess advertiser strength, or understand where an audience comes from. Triggers on: "analyze traffic for [domain]", "how much traffic does [site] get", "compare traffic between [site A] and [site B]", "is [program] worth promoting based on traffic", "traffic analysis", "website analytics for [domain]", "where does [site] get traffic"…

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

It sits in Marketing & SEO, covering Link building, Product metrics and Influencer and creator marketing. The repository describes itself as: 50 AI agent skills for affiliate marketing. Research trending content, write data-backed posts, generate infographics, build landing pages, deploy — full flywheel with social… The licence is MIT.

When your agent uses it

  • Evaluate affiliate program websites
  • Compare competitor traffic
  • Assess advertiser strength
  • Understand where an audience comes from

Example prompts

  • “analyze traffic for [domain]”
  • “how much traffic does [site] get”
  • “compare traffic between [site A] and [site B]”
  • “/traffic-analyzer”

Requirements

  • Compatibility (from SKILL.md): Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Gather Traffic Data
  2. Analyze Core Metrics
  3. Interpret for Use Case
  4. Generate Traffic Score
  5. Compare (if multiple domains)
  6. Self-Validation

What it can do on your machine

Read from SKILL.md and the folder at commit e43bfae. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • similarweb.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent

    From compatibility in the SKILL.md frontmatter.

Context cost

Traffic Analyzer loads about 3.7k tokens when it runs. Until then it costs about 191 tokens; SKILL.md has 1,136 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~191
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Affitor/affiliate-skills at commit e43bfae, republished under its MIT licence (© Affitor). 1,136 words, ~3,726 tokens.

Download SKILL.mdSave it as .claude/skills/traffic-analyzer/SKILL.md (or your agent's skills folder).
name
traffic-analyzer
description
Analyze website traffic, global rank, engagement metrics, and traffic sources for any domain. Use this skill to evaluate affiliate program websites, compare competitor traffic, assess advertiser strength, or understand where an audience comes from. Triggers on: "analyze traffic for [domain]", "how much traffic does [site] get", "compare traffic between [site A] and [site B]", "is [program] worth promoting based on traffic", "traffic analysis", "website analytics for [domain]", "where does [site] get traffic", "check if [advertiser] is legit", "evaluate [program] website health", "SimilarWeb analysis", "traffic sources for [domain]", "how popular is [site]", "website rank", "domain authority check", "compare affiliate program websites".
compatibility
Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent
license
MIT
version
1.0.0
tags
affiliate-marketing, research, traffic, analytics, competitor-analysis, advertiser-evaluation
metadata.author
affitor
metadata.version
1.0
metadata.stage
S1-Research

Traffic Analyzer

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:

  • Is this affiliate program's website healthy? (High traffic = more brand awareness = easier conversions)
  • Where does a competitor get their traffic? (Find channels they're ignoring)
  • Compare 2-3 affiliate programs by advertiser website strength
  • Validate a niche by checking traffic to the top programs in it

Stage

This skill belongs to Stage S1: Research

When to Use

  • Before committing to promote an affiliate program — check if the advertiser is legit
  • When comparing multiple programs — traffic is a proxy for brand strength
  • When competitor-spy identifies competitor sites — analyze their traffic sources
  • When evaluating a niche — check if the top programs have healthy traffic
  • When an advertiser claims "millions of users" — verify with data

Input Schema

yaml
domains: 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

Workflow

Step 1: Gather Traffic Data

With SimilarWeb API (see shared/references/social-data-providers.md):

If social_data_config.similarweb is configured:

  • Call SimilarWeb API for each domain
  • Returns: global rank, country rank, visits, pages/visit, avg duration, bounce rate, traffic sources

Without API (web_search fallback):

For each domain:

  1. web_search "[domain] traffic similarweb" → often shows rank and visit estimates in snippets
  2. web_search "[domain] site traffic statistics" → third-party reports
  3. web_search "site:[domain]" → Google index count as proxy for content depth
  4. web_search "[domain] alexa rank" OR "[domain] semrush traffic" → alternative sources
  5. web_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.

Step 2: Analyze Core Metrics

For each domain, analyze and interpret:

Traffic Volume:

yaml
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:

yaml
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:

yaml
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)
Step 3: Interpret for Use Case

For affiliate promoters (focus: "affiliate"):

Score the domain as an affiliate promotion target:

SignalGood (8-10)OK (5-7)Red Flag (1-4)
Monthly visits>500K50K-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>42-4<2

Why this matters for affiliates:

  • High traffic = people already search for this brand → easier to convert your referrals
  • Strong brand (high direct traffic) = trust → higher conversion rate
  • Good engagement = product delivers value → lower refund rate → your commissions stick
  • Healthy search traffic = sustainable business → long-term commission potential
  • High paid traffic = advertiser invests in growth → good sign for program longevity

For competitor analysis (focus: "competitor"):

  • Identify their strongest traffic channel → where are they winning?
  • Find their weakest channel → opportunity for you
  • Compare bounce rate → are they retaining visitors better than you?
  • Check referral traffic → which sites link to them? (potential partnership targets)

For advertiser evaluation (focus: "advertiser"):

  • Is the advertiser's website healthy? (declining traffic = risky to promote)
  • Do they invest in marketing? (paid traffic % shows ad budget)
  • Is their product sticky? (engagement metrics reveal product quality)
  • How established are they? (global rank trajectory)
Step 4: Generate Traffic Score

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:

  • 80-100: Excellent. Strong, established brand. Safe to promote long-term.
  • 60-79: Good. Healthy traffic. Solid promotion candidate.
  • 40-59: Fair. Growing or niche site. Evaluate other factors (commission, product quality).
  • 20-39: Weak. Low traffic or declining. Proceed with caution.
  • 0-19: Red flag. Very low traffic, new, or declining fast. Not recommended unless early-stage with high commission.
Step 5: Compare (if multiple domains)

If 2+ domains provided, create side-by-side comparison:

  • Which has more traffic?
  • Which has better engagement?
  • Which has more diverse traffic sources?
  • Which is growing faster?
  • Overall winner with reasoning
Step 6: Self-Validation

Before presenting output, verify:

  • Data source clearly stated (API vs web_search estimate)
  • Scores are calibrated (not all 8/10 — differentiate clearly)
  • Interpretation matches the focus (affiliate vs competitor vs advertiser)
  • Red flags explicitly called out, not buried
  • Recommendation is actionable and specific

If any check fails, fix before delivering. Do not flag checklist to user.

Output Schema

yaml
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

Output Format

markdown
## 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
Show full SKILL.md (467 more words)Show less

Error Handling

  • No API and web_search returns limited data: Present what's available. Note: "Limited data available via web search. For accurate metrics, configure SimilarWeb API — see shared/references/social-data-providers.md." Still provide estimated score.
  • Domain not found / too new: Note: "[domain] has insufficient traffic data. This could mean: (1) very new site, (2) very low traffic, (3) data not yet indexed. This is itself useful information — proceed with caution." Score: 10/100.
  • Domain is a subdomain: Analyze the root domain instead. Note the adjustment.
  • More than 5 domains requested: Analyze top 5, suggest running again for the rest.
  • SimilarWeb API rate limited: Fall back to web_search for remaining domains.

Examples

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."

Feedback & Issue Reporting

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:

  • Domain not found in SimilarWeb: Very new or very small site. Report as data_quality, note domain.
  • All metrics null from web_search: No traffic data findable. Report as data_quality, severity: medium.
  • Traffic score seems wrong: Score doesn't match known reality (e.g., Google.com scored 40/100). Report as wrong_output.

Auto-detect triggers:

  • traffic_score is 0 or null for a well-known domain
  • All traffic_sources percentages are null
  • Comparison requested but only 1 domain returned data

Report issues: GitHub Issues | Discussions

References

  • shared/references/social-data-providers.md — SimilarWeb API configuration
  • shared/references/flywheel-connections.md — master flywheel connection map
  • shared/references/affiliate-glossary.md — affiliate marketing terminology
  • shared/references/feedback-protocol.md — issue detection and reporting standard

Flywheel Connections

Feeds Into
  • affiliate-program-search (S1) — traffic score as program evaluation factor
  • competitor-spy (S1) — traffic sources reveal competitor strategy
  • niche-opportunity-finder (S1) — traffic data validates niche demand
  • content-angle-ranker (S1) — traffic source breakdown informs platform prioritization
  • trending-content-scout (S1) — social traffic % hints at which platforms to scout
Fed By
  • competitor-spy (S1) — competitor domains to analyze
  • affiliate-program-search (S1) — program URLs to evaluate
  • niche-opportunity-finder (S1) — top program domains in a niche
Feedback Loop
  • S6 performance-report shows your referral contribution to the advertiser → compare your traffic impact over time → prioritize programs where you move the needle
yaml
chain_metadata:
  skill_slug: "traffic-analyzer"
  stage: "research"
  timestamp: string
  suggested_next:
    - "affiliate-program-search"
    - "competitor-spy"
    - "trending-content-scout"

© Affitor, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/research/traffic-analyzer of Affitor/affiliate-skills.

Open the folder on GitHubat commit e43bfae

Compare with similar skills

Traffic Analyzer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Traffic Analyzer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Traffic Analyzer this skillAffitor/affiliate-skills698—~3.7kAutomated safety check: PassMIT
FLOW SEO FrameworkAgriciDaniel/claude-seo18k2 repos~1.4kAutomated safety check: PassMIT
SEO DataforseoAgriciDaniel/codex-seo7872 repos~4.6kAutomated safety check: PassMIT
Backlink CheckRyze-AI-Adgent/open-seo-mcp-skills4.4k—~515Automated safety check: PassMIT
Beyondseobeyondtahir/beyondseo155—~4.3kAutomated safety check: PassMIT
Webobsidianxnohat/webobsidian268—~2.1kAutomated safety check: PassMIT

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Categories

Questions about Traffic Analyzer

What does Traffic Analyzer do?

Analyze website traffic, global rank, engagement metrics, and traffic sources for any domain. Traffic Analyzer is an agent skill from Affitor/affiliate-skills. Analyze website traffic, global rank, engagement metrics, and traffic sources for any domain.

When should I use Traffic Analyzer?

Traffic Analyzer fits situations like: evaluate affiliate program websites; compare competitor traffic; assess advertiser strength; understand where an audience comes from.

How do I install Traffic Analyzer in Claude Code?

Run `npx skills add Affitor/affiliate-skills --skill traffic-analyzer -a claude-code`. Or copy the skill folder (skills/research/traffic-analyzer in Affitor/affiliate-skills) into .claude/skills/traffic-analyzer in your project. Claude Code loads it when a task matches its description.

How do I install Traffic Analyzer in Codex?

Run `npx skills add Affitor/affiliate-skills --skill traffic-analyzer -a codex`. Or copy the skill folder (skills/research/traffic-analyzer in Affitor/affiliate-skills) into .agents/skills/traffic-analyzer in your project. Codex loads it when a task matches its description.

Can I use Traffic Analyzer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Affitor/affiliate-skills --skill traffic-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/traffic-analyzer, .gemini/skills/traffic-analyzer, .github/skills/traffic-analyzer and .opencode/skills/traffic-analyzer in your project.

What does Traffic Analyzer need to run?

SKILL.md names no scripts, command-line tools or credentials: Traffic Analyzer is instructions for the agent only. Compatibility (from SKILL.md): Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent.

Does Traffic Analyzer access the network?

SKILL.md names 1 domain. In commands or code: similarweb.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Traffic Analyzer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Traffic Analyzer use?

Traffic Analyzer is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Traffic Analyzer use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Traffic Analyzer?

Skills that share tags, products or a category with Traffic Analyzer: FLOW SEO Framework (AgriciDaniel/claude-seo, 18k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 787 stars), Backlink Check (Ryze-AI-Adgent/open-seo-mcp-skills, 4.4k stars) and Beyondseo (beyondtahir/beyondseo, 155 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Traffic Analyzer?

Affitor (a GitHub organization) maintains it in Affitor/affiliate-skills, which has 698 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on September 15, 2026.

Source: Affitor/affiliate-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.