Agent skill

Analytics Tracking

by borghei in borghei/Claude-Skills

End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy.

MITAuto-check passedMarketing & SEO

Install Analytics Tracking

skills CLI
$ npx skills add borghei/Claude-Skills --skill analytics-tracking -a claude-code

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

GitHub CLI
$ gh skill install borghei/Claude-Skills analytics-tracking --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/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/marketing/analytics-tracking .claude/skills/analytics-tracking && 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
analytics-tracking
GitHub stars
874
Token cost
~5.7k tokens
SKILL.md length
2,333 words
Files
4 (incl. scripts)
Skills in repo
364
Repo updated
First seen
Licence
MIT

At a glance

End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy.

  • Works in 5 steps: Always noun_verb order, never verb_noun → Snake_case only -- no camelCase, no… → Past tense verbs: _started, _completed,… → …
  • Building a tracking plan
  • SKILL.md covers Overview, Clarify First, Operating Modes and Event Taxonomy Design, plus 5 more sections
  • Runs Python scripts from its folder; calls python

What it does

Analytics Tracking is an agent skill from borghei/Claude-Skills. End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy. Use when building a tracking plan, debugging missing events, setting up GTM, or auditing existing analytics.

Its SKILL.md is about 5.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `scripts/event_schema_checker.py`, `scripts/funnel_drop_off_analyzer.py` and `scripts/utm_validator.py`).

It sits in Marketing & SEO, covering Product analytics, Marketing analytics and Go-to-market strategy. It works with Google Analytics. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.

When your agent uses it

  • Building a tracking plan
  • Debugging missing events
  • Auditing existing analytics

Example prompts

  • “/analytics-tracking”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Always noun_verb order, never verb_noun
  2. Snake_case only -- no camelCase, no hyphens, no PascalCase
  3. Past tense verbs: _started, _completed, _failed, _viewed
  4. Specific enough to be unambiguous, not so verbose it is a sentence
  5. Prefix with domain when needed: onboarding_step_completed, billing_plan_selected

What it can do on your machine

Read from SKILL.md and the folder at commit c9a1487. 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

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

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

  • Network

    Links to these hosts (documentation or services it may open):

    • support.google.com
    • help.openai.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.

Context cost

Analytics Tracking loads about 5.7k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 2,333 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~5.7k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from borghei/Claude-Skills at commit c9a1487, republished under its MIT licence (© borghei). 2,333 words, ~5,735 tokens.

Download SKILL.mdSave it as .claude/skills/analytics-tracking/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
analytics-tracking
description
End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy. Use when building a tracking plan, debugging missing events, setting up GTM, or auditing existing analytics.
license
MIT + Commons Clause
metadata.version
1.0.0
metadata.author
borghei
metadata.category
marketing
metadata.domain
analytics-implementation
metadata.updated
2026-09-21
metadata.frameworks
ga4, gtm, event-taxonomy, conversion-tracking

Analytics Tracking - Implementation & Auditing

Category: Marketing Tags: GA4, Google Tag Manager, event tracking, conversion tracking, UTM, analytics audit, consent mode

Overview

Analytics Tracking is the implementation layer for marketing measurement. Bad tracking is worse than no tracking -- duplicate events, missing parameters, unconsented data, and broken conversions lead to decisions based on bad data. This skill covers building tracking right the first time and finding what is broken when it is not.

This skill handles implementation only. For analyzing campaign performance data, use campaign-analytics. For product analytics and in-app behavior, use the product-team skills.


Clarify First

Before building the tracking plan, confirm these inputs. If any is unknown or vague, ASK — do not assume:

  • Operating mode — build from scratch, audit existing, or debug a specific issue (selects the entire workflow)
  • Platform stack — GA4, GTM, and which ad platforms (Google Ads / Meta / LinkedIn) (drives implementation + conversion tracking setup)
  • Key conversions + funnel events — the user actions that matter to the business (drives event taxonomy + conversion configuration)
  • Region / consent requirements — EU/EEA users present? (determines whether Consent Mode v2 is required)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Operating Modes

Mode 1: Build From Scratch

No analytics in place. Build the tracking plan, implement GA4 + GTM, define event taxonomy, configure conversions.

Mode 2: Audit Existing Tracking

Tracking exists but data cannot be trusted. Audit coverage, identify gaps, clean up duplicates, fix consent issues.

Mode 3: Debug Specific Issues

Events are missing, conversions do not match, GTM preview shows fires but GA4 does not record. Structured debugging workflow.


Event Taxonomy Design

Get this right before touching GA4 or GTM. Retrofitting taxonomy is painful and expensive.

Naming Convention

Format: object_action (snake_case, past tense verb)

CorrectWrongWhy Wrong
form_submittedsubmitFormcamelCase, verb-first
plan_selectedclickPricingPlanImplementation detail, not user action
video_startedVideoStartPascalCase, inconsistent tense
checkout_completedpurchaseAmbiguous, not a verb phrase

Rules:

  1. Always noun_verb order, never verb_noun
  2. Snake_case only -- no camelCase, no hyphens, no PascalCase
  3. Past tense verbs: _started, _completed, _failed, _viewed
  4. Specific enough to be unambiguous, not so verbose it is a sentence
  5. Prefix with domain when needed: onboarding_step_completed, billing_plan_selected
Standard Event Parameters

Every custom event should include applicable parameters from this table:

ParameterTypeExampleRequired When
user_idstringusr_abc123Always (if authenticated)
plan_namestringprofessionalBilling/pricing events
valuenumber99.00Revenue events
currencystringUSDAlways with value
content_groupstringonboardingPage/flow grouping
methodstringgoogle_oauthSignup/login events
step_namestringconnect_accountMulti-step flows
step_numbernumber3Multi-step flows
sourcestringpricing_pageCTA click events
SaaS Event Taxonomy (Reference)

Core Funnel:

visitor_arrived              (automatic page_view in GA4)
signup_started               (user clicked "Sign up")
signup_completed             (account created)
trial_started                (free trial began)
onboarding_step_completed    (params: step_name, step_number)
feature_activated            (params: feature_name)
plan_selected                (params: plan_name, billing_period)
checkout_started             (params: value, currency, plan_name)
checkout_completed           (params: value, currency, transaction_id)
subscription_renewed         (params: value, plan_name)
subscription_cancelled       (params: cancel_reason, plan_name)

Micro-Conversions:

pricing_viewed
demo_requested               (params: source)
form_submitted               (params: form_name, form_location)
content_downloaded           (params: content_name, content_type)
video_started                (params: video_title)
video_completed              (params: video_title, percent_watched)
chat_opened
help_article_viewed          (params: article_name)
invite_sent                  (params: recipient_role)
integration_connected        (params: integration_name)

GA4 Configuration

Data Stream Setup
  1. Create property: GA4 Admin > Properties > Create
  2. Add web data stream with your domain
  3. Enhanced Measurement -- review each:
    • Page views: Keep enabled
    • Scrolls: Keep enabled
    • Outbound clicks: Keep enabled
    • Site search: Enable if you have search
    • Video engagement: Disable if tracking videos manually (avoids duplicates)
    • File downloads: Disable if tracking via GTM (for better parameters)
  4. Configure domains: add all subdomains in your funnel
  5. Data retention: Set to 14 months (maximum for free GA4)
Key Events (formerly "Conversions")

GA4 renamed "conversions" to key events in March 2024; "conversions" now refers to key events imported into Google Ads. Mark as key events in GA4 Admin > Data display > Events (star icon):

  • signup_completed
  • checkout_completed
  • demo_requested
  • trial_started

Rules:

  • Maximum 30 key events per standard property (50 on Analytics 360) -- curate carefully
  • Marking a key event is not retroactive -- it affects reports from the time it is marked, not historic data
  • Do not mark micro-conversions as key events unless optimizing ad campaigns for them
  • Counting method: set to "once per session" for lead events, "every" for purchase events

Source: Mark events as key events (as of September 2026).

Custom Dimensions

Register custom dimensions for any event parameter you want to filter/segment by:

ParameterScopeDimension Name
plan_nameEventPlan Name
user_idUserUser ID
content_groupEventContent Group
feature_nameEventFeature Name

Register in GA4 Admin > Custom definitions > Create custom dimension.


Google Tag Manager Implementation

Container Architecture
GTM Container
├── Tags
│   ├── GA4 Configuration (All Pages trigger)
│   ├── GA4 Event Tags (one per custom event)
│   ├── Google Ads Conversion Tags (per conversion action)
│   └── Meta Pixel / LinkedIn Insight (if running ads)
├── Triggers
│   ├── All Pages (Page View)
│   ├── DOM Ready
│   ├── Custom Event triggers (one per dataLayer event)
│   └── Element Click triggers (CSS selector based)
└── Variables
    ├── Data Layer Variables (one per dataLayer key)
    ├── Constants (GA4 Measurement ID, etc.)
    └── Lookup Tables (if needed for mapping)
Implementation Pattern: Data Layer Push

Your application pushes events to the data layer. GTM picks them up and sends to GA4.

Application code:

javascript
// Push event when user completes signup
window.dataLayer = window.dataLayer || [];
window.dataLayer.push({
  event: 'signup_completed',
  method: 'email',
  user_id: userId,
  plan_name: 'trial'
});

GTM configuration:

Trigger:
  Type: Custom Event
  Event name: signup_completed

Tag:
  Type: GA4 Event
  Event name: signup_completed
  Parameters:
    method:    {{DLV - method}}
    user_id:   {{DLV - user_id}}
    plan_name: {{DLV - plan_name}}
SPA Handling

Single Page Applications need special attention because page views do not fire automatically on route changes.

Option A: History change trigger (GTM built-in)

  • Enable "History Change" trigger in GTM
  • Fires GA4 page_view on every pushState/popState

Option B: DataLayer push on route change (more control)

javascript
// In your router (React Router, Next.js, etc.)
router.events.on('routeChangeComplete', (url) => {
  window.dataLayer.push({
    event: 'page_view',
    page_location: url,
    page_title: document.title
  });
});

Conversion Tracking: Ad Platforms

Google Ads

Recommended approach: Import GA4 conversions into Google Ads (single source of truth).

  1. Link GA4 and Google Ads accounts
  2. In Google Ads > Goals > Conversions > Import > Google Analytics
  3. Select GA4 key events to import (they become Google Ads conversions)
  4. Set attribution model: Data-driven (if 50+ conversions/month), otherwise Last-click
  5. Conversion window: 30 days for lead gen, 90 days for high-consideration B2B

Enhanced Conversions: Enable for 15-30% better conversion measurement. Sends hashed first-party data (email, phone) to match conversions that cookies miss.

Meta (Facebook/Instagram)
  1. Install Meta Pixel base code via GTM
  2. Configure standard events: PageView, Lead, CompleteRegistration, Purchase
  3. Conversions API (CAPI): strongly recommended -- client-side pixel loses approximately 30% of conversions due to ad blockers and iOS App Tracking Transparency
  4. Deduplication: when using both pixel and CAPI, send the same event_id to prevent double-counting
LinkedIn Insight Tag
  1. Install via GTM (Tag type: LinkedIn Insight)
  2. Configure conversion events in LinkedIn Campaign Manager
  3. Match events to your taxonomy: signup_completed -> LinkedIn "Sign-up" conversion

UTM Strategy

Convention Enforcement
ParameterConventionExample
utm_sourcePlatform name, lowercasegoogle, linkedin, newsletter
utm_mediumTraffic typecpc, email, social, organic
utm_campaignCampaign identifierq1-trial-push, brand-awareness-2026
utm_contentCreative varianthero-cta-blue, sidebar-text-link
utm_termPaid keyword (search only)saas-analytics-tool

Critical rules:

  • Never tag organic traffic with UTMs (overrides GA4 automatic attribution)
  • Never tag direct/internal links with UTMs
  • Use a UTM builder spreadsheet or tool -- manual entry causes inconsistency
  • Lowercase everything -- Google and google are different sources in GA4
Attribution Windows
PlatformDefaultRecommended for SaaS
GA430 days30-90 days (match your sales cycle)
Google Ads30 days30 days (trial), 90 days (enterprise)
Meta7-day click, 1-day view7-day click only (view-through inflates; 7-/28-day view windows were removed Jan 2026)
LinkedIn30 days30 days

AI Referral Traffic

Visits from AI assistants (ChatGPT, Gemini, Claude, Copilot, Perplexity, etc.) are a growing, distinct acquisition source. Measure them explicitly instead of letting them blur into Referral or Direct.

GA4 "AI Assistant" Channel (as of September 2026)

Since May 13, 2026, GA4's Default Channel Group includes an AI Assistant channel. When the referrer matches Google's list of recognized AI assistants, GA4 sets medium = ai-assistant and campaign = (ai-assistant), and the session is grouped under AI Assistant. No configuration is needed. The rule is evaluated before Referral. Sources: Default channel group, What's new in Google Analytics.

Known Gaps
GapWhat happensMitigation
Not retroactiveSessions before the rollout stay in ReferralUse the custom channel group below for historical comparison
Unrecognized assistantsAI tools not on Google's list still land in ReferralCustom channel group with your own regex
Google AI Overviews / AI Mode clicksExcluded from AI Assistant; they arrive from google.com and count as Organic SearchUse Search Console (Web search type + Generative AI report) — GA4 cannot isolate them
Referrer strippedMany app and copy-paste visits arrive with no referrer and fall into DirectAdd UTMs to links you control (e.g., in llms.txt, docs, GPT/app listings); watch Direct landing pages that match AI-cited pages
Assistant-added UTMsSome assistants append their own UTM (ChatGPT adds utm_source=chatgpt.com to referral links, per OpenAI's publisher FAQ), which changes how source/medium are recordedMatch on session source (which the UTM sets) rather than referrer alone
Fallback: Custom Channel Group

Create a custom channel group in GA4 (Admin > Data display > Channel groups), add an "AI Assistant (custom)" channel above Referral, with the condition Session source matches regex:

^(chatgpt\.com|chat\.openai\.com|openai\.com|perplexity\.ai|www\.perplexity\.ai|gemini\.google\.com|bard\.google\.com|claude\.ai|copilot\.microsoft\.com|edgeservices\.bing\.com|chat\.deepseek\.com|grok\.com|meta\.ai|chat\.mistral\.ai|you\.com|phind\.com)$

Keep the list in version control and review it quarterly; assistant domains change. The campaign-analytics attribution script uses the same list to classify an ai_assistant channel.


Cross-Domain Tracking

For funnels crossing domains (e.g., acme.com to app.acme.com):

  1. GA4 Admin > Data Streams > Configure tag settings > Configure your domains > Add both domains
  2. GTM: GA4 Configuration tag > Fields to Set > linker > Add domains
  3. Admin > Data Streams > List unwanted referrals > Add both domains

Verification: Visit domain A, click link to domain B, check GA4 DebugView. The session should NOT restart. If a new session starts, cross-domain tracking is broken.


Show full SKILL.md (911 more words)Show less

Required for EU compliance and for maintaining data quality in consent-heavy markets.

SettingNo Consent ModeBasicAdvanced
User declines cookiesZero dataZero dataModeled data (GA4 estimates)
Data quality impact25-40% data loss in EU25-40% data loss5-15% data loss
Implementation effortNoneMediumMedium-High

Recommendation: Implement Advanced Consent Mode v2 via GTM with a CMP (Cookiebot, OneTrust, Usercentrics).

Expected consent rates by region:

  • EU/EEA: 60-75%
  • UK: 70-80%
  • US: 85-95%
  • Rest of world: 80-90%
Implementation via GTM
1. Install CMP tag (fires first, before any other tags)
2. Set default consent state:
   - analytics_storage: denied
   - ad_storage: denied
   - ad_user_data: denied
   - ad_personalization: denied
3. CMP updates consent state on user choice
4. GA4 and ad tags respect consent automatically

Data Quality Auditing

Audit Checklist

Event Quality:

  • No duplicate events (check GTM Preview for double-fires)
  • All custom events have required parameters
  • Event names follow naming convention
  • No PII in event parameters (names, emails, phone numbers)
  • Enhanced Measurement not duplicating GTM custom events

Configuration Quality:

  • Data retention set to 14 months
  • Internal traffic filter enabled (office and developer IPs)
  • Bot filtering enabled (default in GA4)
  • Cross-domain tracking working (if applicable)
  • Custom dimensions registered for filtered parameters
  • Conversion events marked correctly

Consent Quality:

  • Consent Mode v2 implemented (if serving EU users)
  • CMP banner appearing on first visit
  • Tags respect consent state (no firing before consent)
  • Consent state persisting across pages
Common Data Quality Issues
IssueSymptomRoot CauseFix
Inflated page views2x expected volumeGTM page_view + Enhanced MeasurementDisable Enhanced page_view
Missing conversionsGA4 and Ads numbers differAttribution window mismatchAlign windows
(not set) pagesPages show as "/(not set)"SPA routing not handledImplement SPA tracking
Self-referralsOwn domain in referral reportMissing cross-domain configAdd domains to referral exclusion
Direct traffic spikePaid traffic showing as directUTMs missing or strippedAudit UTM usage
Zero EU dataNo traffic from EU marketsConsent blocks all trackingImplement Advanced Consent Mode
Debugging Workflow
Step 1: Open GTM Preview mode
  - Is the tag firing? Check triggers and conditions
  - Is the data layer populated? Check dataLayer in console

Step 2: Check GA4 DebugView (Admin > DebugView)
  - Is the event appearing? If yes, GTM is working
  - Are parameters populated? Check parameter values

Step 3: Check GA4 Realtime report
  - Events appearing with 5-minute delay? Normal
  - Events not appearing at all? Check measurement ID

Step 4: Check Network tab (DevTools)
  - Filter by "collect" or "analytics"
  - Is the request being sent? Check status code
  - Is the request being blocked? Check ad blockers / consent

Proactive Triggers

Surface these findings without being asked:

  • Events firing on every page load with identical parameters: misconfigured trigger causing data inflation
  • No user_id parameter on authenticated events: cannot connect analytics to CRM or understand cohorts
  • GA4 conversion count differs from Google Ads by more than 15%: attribution window or deduplication issue
  • No consent mode in EU markets: legal exposure and 25-40% data underreporting
  • All pages showing as /(not set): SPA routing not handled properly
  • utm_source showing as direct for known paid campaigns: UTMs missing or being stripped by redirects

SkillUse When
campaign-analyticsAnalyzing marketing performance and channel ROI (not implementation)
ab-test-setupDesigning experiments (this skill's events feed A/B tests)
launch-strategyTracking events for product launches
email-sequenceSetting up email click tracking and UTM parameters

Troubleshooting

SymptomLikely CauseResolution
GA4 shows 50% less traffic than expected after privacy changesClient-side tracking blocked by ad blockers and ITP/ETP cookie expiryImplement server-side GTM tagging — recovers 20-40% of lost attribution data within first quarter
Conversion counts differ between GA4 and Google Ads by >15%Attribution window mismatch or deduplication failure between pixel and CAPIAlign attribution windows across platforms and ensure matching event_id for deduplication
Events fire in GTM Preview but do not appear in GA4 reportsMeasurement ID mismatch, consent mode blocking, or data processing delayCheck Measurement ID in GA4 Configuration tag, verify consent state, wait 24-48 hours for standard reports
UTM parameters show as (not set) in GA4UTMs stripped by redirects, social platform link wrappers, or internal links overwritingAudit redirect chains, use UTM-safe shorteners, never tag internal links with UTMs
Server-side container returns 400 errorsMalformed event payload or missing required fields in Measurement Protocol requestsValidate payload against GA4 Measurement Protocol schema, check required client_id and api_secret
Enhanced Measurement duplicating custom GTM eventsBoth Enhanced Measurement and GTM firing the same event type (e.g., page_view, scroll)Disable the overlapping Enhanced Measurement toggle for events you track via GTM
Consent Mode v2 reporting zero EU data instead of modeled dataDefault consent state not set before GA4 tag fires, or CMP not updating consent correctlyEnsure consent defaults fire as the very first tag in GTM before all other tags

Success Criteria

  • All custom events follow consistent noun_verb snake_case naming convention with zero violations in schema audit
  • GA4 conversion counts match ad platform conversion counts within 10% variance
  • Server-side tracking recovers 20%+ of previously lost attribution data within 90 days of deployment
  • UTM parameter validation passes 100% on all active campaigns (no mixed case, no spaces, no missing required params)
  • Consent Mode v2 limits EU data loss to under 15% via behavioral modeling
  • Event parameters contain zero PII violations as verified by automated schema checker
  • Data retention set to 14 months, internal traffic filtered, and cross-domain tracking verified

Scope & Limitations

In Scope: GA4 configuration, GTM implementation, event taxonomy design, conversion tracking setup, UTM strategy, consent management, data quality auditing, server-side tagging architecture, cross-domain tracking, ad platform conversion integration (Google Ads, Meta, LinkedIn).

Out of Scope: Product analytics platforms (Amplitude, Mixpanel), data warehouse configuration, custom ETL pipelines, mobile app tracking (Firebase), marketing attribution modeling (see marketing-analyst skill), A/B test statistical analysis (see ab-test-setup skill).

Limitations: Server-side tracking requires a cloud-hosted GTM container (GCP, AWS, or third-party) with associated infrastructure costs. Privacy-first analytics with Consent Mode v2 produces modeled data for non-consented users — modeled data has 5-15% variance from actual. This skill does not make LLM or API calls; all validation is deterministic.


Scripts

ScriptPurposeUsage
scripts/utm_validator.pyValidate UTM parameters for consistency and naming conventionspython scripts/utm_validator.py urls.csv --json
scripts/event_schema_checker.pyValidate event names and parameters against taxonomy, detect PIIpython scripts/event_schema_checker.py events.json --json
scripts/funnel_drop_off_analyzer.pyAnalyze conversion funnels and identify biggest drop-off pointspython scripts/funnel_drop_off_analyzer.py --stages "Visitors:10000,Signups:1200,Paid:120"

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

Files

SKILL.md and 3 other files (scripts) in marketing/analytics-tracking of borghei/Claude-Skills.

  • SKILL.md
  • scripts/event_schema_checker.py
  • scripts/funnel_drop_off_analyzer.py
  • scripts/utm_validator.py

Open the folder on GitHubat commit c9a1487

Compare with similar skills

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    Idea to AI-generated prototype to customer validation to engineering handoff.

    874 GitHub stars~3.6k tokensUpdated today
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  • Analytics Engineer

    borghei/Claude-Skills

    Analytics engineering across data modeling, dbt, transformation, and semantic layers.

    874 GitHub stars~3.4k tokensUpdated today
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  • Ansoff Matrix

    borghei/Claude-Skills

    Ansoff Matrix — 4-quadrant framework for growth options: market penetration, market/product development, and diversification.

    874 GitHub stars~2.2k tokensUpdated today
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  • Brainstorm Okrs

    borghei/Claude-Skills

    OKR brainstorming and validation using the Radical Focus framework — outcome objectives, measurable key results, counter-metrics.

    874 GitHub stars~1.4k tokensUpdated today
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Questions about Analytics Tracking

What does Analytics Tracking do?

End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy. Analytics Tracking is an agent skill from borghei/Claude-Skills. End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy.

When should I use Analytics Tracking?

Analytics Tracking fits situations like: building a tracking plan; debugging missing events; auditing existing analytics.

How do I install Analytics Tracking in Claude Code?

Run `npx skills add borghei/Claude-Skills --skill analytics-tracking -a claude-code`. Or copy the skill folder (marketing/analytics-tracking in borghei/Claude-Skills) into .claude/skills/analytics-tracking in your project. Claude Code loads it when a task matches its description.

How do I install Analytics Tracking in Codex?

Run `npx skills add borghei/Claude-Skills --skill analytics-tracking -a codex`. Or copy the skill folder (marketing/analytics-tracking in borghei/Claude-Skills) into .agents/skills/analytics-tracking in your project. Codex loads it when a task matches its description.

Can I use Analytics Tracking 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 borghei/Claude-Skills --skill analytics-tracking -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analytics-tracking, .gemini/skills/analytics-tracking, .github/skills/analytics-tracking and .opencode/skills/analytics-tracking in your project.

What does Analytics Tracking need to run?

Going by SKILL.md and its folder, Analytics Tracking needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Analytics Tracking access the network?

SKILL.md names 2 domains. As links in the text: support.google.com and help.openai.com. This is read from the text; nothing was executed.

Is Analytics Tracking 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Analytics Tracking use?

Analytics Tracking 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 Analytics Tracking use?

About 5.7k tokens (SKILL.md is roughly 23k 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 Analytics Tracking?

Skills that share tags, products or a category with Analytics Tracking: Analytics (Nexus-JPF/note-companion, 869 stars), Tracking Schema (jtrackingai/analytics-tracking-automation, 142 stars), Gtm Tracking Plan (cognyai/claude-code-marketing-skills, 104 stars) and Paw Mkt Analytics (pawbytes/skill-suites, 110 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analytics Tracking?

borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 874 GitHub stars. The repository holds 364 skills in this directory. The repository was last updated on October 7, 2026.

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