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Analytics Reporting

skill-arturseo-geo-claude-code-skills-analytics-reporting · by arturseo-geo

A Claude skill from arturseo-geo/claude-code-skills.

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Install

$ agentstack add skill-arturseo-geo-claude-code-skills-analytics-reporting

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Analytics & Reporting Skill

When This Skill Activates

This skill loads automatically when you mention:

  • analytics, reporting, traffic metrics, performance reports
  • weekly reports, monthly reports, dashboards, data analysis
  • traffic drops, traffic spikes, content performance, page performance
  • user behavior, conversion analysis, cross-source data correlation
  • why did traffic drop, what content is performing, performance anomaly detection
  • trend analysis, root cause analysis, traffic investigation
  • combined reporting, GSC + GA4 analysis, search traffic, organic traffic trends
  • bounce rate analysis, engagement metrics, landing page analysis
  • session analysis, revenue correlation, goal conversion
  • heat maps, user journeys, content audit performance, traffic forecasting
  • any multi-source data analysis and reporting task

Data Sources

Real-time APIs:

  • Google Search Console API (impressions, clicks, CTR, position, queries)
  • Google Analytics 4 API (property 528383456) — sessions, users, conversions, events
  • PostgreSQL OpenSEO DB (100.87.191.9:5432) — internal metrics, backlinks, keywords
  • Redis cache (100.87.191.9:6379) — geolab-links queue state, job timing

WordPress & VPS:

  • WordPress REST API (thegeolab.net) — post metadata, publish dates, author
  • VPS Service APIs (100.87.191.9):
  • seo-intelligence (:3001) — rank tracking data
  • geolab-links (:3002) — link profile, authority scores
  • geolab-backlinks (:4000) — backlink snapshots, competitor data
  • geolab-keywords (:4001) — keyword clustering, SERP features
  • geolab-writer (:4002) — published content, performance tags

Core Responsibilities

  1. Multi-Source Correlation — Join data from GSC, GA4, PostgreSQL, WordPress, Redis using lag-aware joins and confidence scoring
  2. Anomaly Detection — Z-score, moving averages, seasonality adjustment, algorithm change detection, composite anomaly scoring
  3. Report Generation — Weekly summaries, monthly deep-dives, investigation reports, audit snapshots, page-level breakdowns
  4. Actionable Insights — Root cause analysis, content recommendations, traffic recovery strategies, opportunity detection
  5. Data Validation — Check data completeness, lag detection, source freshness, accuracy within confidence bounds

Key Patterns

Data Joining Strategy

  • GSC → GA4: Join on page URL, account for 1-3 day GSC reporting lag
  • GA4 → PostgreSQL: Join on post_id via WordPress URL parsing
  • WordPress → VPS Services: Query via REST API for metadata enrichment
  • Confidence Scoring: Apply weights based on data freshness and source reliability

Anomaly Detection Method

  1. Calculate baseline (30-90 day rolling average)
  2. Adjust for seasonality (day-of-week, holidays, known events)
  3. Compute z-score and isolation forest scores
  4. Combine into composite anomaly score
  5. Flag if score > threshold + explanation

Report Template Structure

  • Executive summary (1 paragraph)
  • Key metrics table (YoY/MoM % change)
  • Anomaly findings (if any)
  • Content performance ranking
  • Traffic sources breakdown
  • Conversion funnel analysis
  • Root cause diagnosis (for drops)
  • Actionable recommendations (3-5 items)
  • Data quality notes + sources cited

Output Standards

Always include:

  • Data date range ("Jan 1-31, 2026")
  • All sources used (GSC API, GA4, PostgreSQL, etc.)
  • Confidence levels (95%, 85%, unvalidated)
  • Actionable recommendations (not just observations)
  • Any caveats or data gaps

Never:

  • Fabricate data or fill gaps with estimates
  • Claim confidence >95% without 3+ sources
  • Recommend without understanding intent
  • Ignore seasonal patterns without mentioning them
  • Skip data freshness checks

See Also

  • anomaly-detection.md — Z-score formulas, moving averages, seasonality math
  • correlation.md — Multi-source joining strategy, lag-aware logic, confidence scoring
  • data-sources.md — API endpoints, query patterns, connection strings
  • report-templates.md — Weekly, monthly, investigation, audit, page-level templates

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.