rank-tracker▌
aaron-he-zhu/seo-geo-claude-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Track keyword rankings over time with trend analysis, movement detection, and competitive benchmarking.
- ›Records and monitors keyword positions across traditional SERPs and AI-generated responses, with historical trend analysis and significant movement alerts
- ›Tracks SERP features (featured snippets, PAA, image/video packs) and AI Overview citation rates for comprehensive search visibility
- ›Compares rankings against competitors with share-of-voice metrics and head-to-head keyword analys
Rank Tracker
SEO & GEO Skills Library · 20 skills for SEO + GEO · ClawHub · skills.sh System Mode: This monitoring skill follows the shared Skill Contract and State Model.
Tracks, analyzes, and reports on keyword ranking positions over time. Monitors both traditional SERP rankings and AI/GEO visibility to provide comprehensive search performance insights.
System role: Monitoring layer skill. It turns performance changes into deltas, alerts, and next actions.
When This Must Trigger
Use this when the conversation involves any of these situations — even if the user does not use SEO terminology:
Use this whenever the task needs time-aware change detection, escalation, or stakeholder-ready visibility.
- Setting up ranking tracking for new campaigns
- Monitoring keyword position changes
- Analyzing ranking trends over time
- Comparing rankings against competitors
- Tracking SERP feature appearances
- Monitoring AI Overview inclusions
- Creating ranking reports for stakeholders
What This Skill Does
- Position Tracking: Records and tracks keyword rankings
- Trend Analysis: Identifies ranking patterns over time
- Movement Detection: Flags significant position changes
- Competitor Comparison: Benchmarks against competitors
- SERP Feature Tracking: Monitors featured snippets, PAA
- GEO Visibility Tracking: Tracks AI citation appearances
- Report Generation: Creates ranking performance reports
Quick Start
Start with one of these prompts. Finish with a short handoff summary using the repository format in Skill Contract.
Set Up Tracking
Set up rank tracking for [domain] targeting these keywords: [keyword list]
Analyze Rankings
Analyze ranking changes for [domain] over the past [time period]
Compare to Competitors
Compare my rankings to [competitor] for [keywords]
Generate Reports
Create a ranking report for [domain/campaign]
Skill Contract
Expected output: a delta summary, alert/report output, and a short handoff summary ready for memory/monitoring/.
- Reads: current metrics, previous baselines, alert thresholds, and reporting context from CLAUDE.md and the shared State Model when available.
- Writes: a user-facing monitoring deliverable plus a reusable summary that can be stored under
memory/monitoring/. - Promotes: significant changes, confirmed anomalies, and follow-up actions to
memory/open-loops.mdandmemory/decisions.md. - Next handoff: use the
Next Best Skillbelow when a change needs action.
Data Sources
Note: All integrations are optional. This skill works without any API keys — users provide data manually when no tools are connected.
See CONNECTORS.md for tool category placeholders.
With ~~SEO tool + ~~search console + ~~analytics + ~~AI monitor connected: Automatically pull ranking positions from ~~SEO tool, search impressions/clicks from ~~search console, traffic data from ~~analytics, and AI Overview citation tracking from ~~AI monitor. Daily automated rank checks with historical trend data.
With manual data only: Ask the user to provide:
- Keyword ranking positions (current and historical if available)
- Target keyword list with search volumes
- Competitor domains and their ranking positions for key terms
- SERP feature status (featured snippets, PAA appearances)
- AI Overview citation data (if tracking GEO metrics)
Proceed with the full analysis using provided data. Note in the output which metrics are from automated collection vs. user-provided data.
Instructions
When a user requests rank tracking or analysis:
-
Set Up Keyword Tracking -- Configure domain, location, device, language, update frequency. Add keywords with volume, current rank, type, and priority. Set up competitor tracking and keyword categories (brand/product/informational/commercial).
-
Record Current Rankings -- Ranking overview by position range (#1, #2-3, #4-10, #11-20, etc.), position distribution visualization, detailed rankings with URL, SERP features, and change.
-
Analyze Ranking Changes -- Overall movement metrics, biggest improvements and declines with hypothesized causes, recommended recovery actions, stable keywords, new rankings, lost rankings.
-
Track SERP Features -- Feature ownership comparison vs competitors (snippets, PAA, image/video pack, local pack), featured snippet status, PAA appearances.
-
Track GEO/AI Visibility -- AI Overview presence per keyword, citation rate and position, GEO performance trend over time, improvement opportunities.
-
Compare Against Competitors -- Share of voice table, head-to-head comparison per keyword, competitor movement alerts with threat level.
-
Generate Ranking Report -- Executive summary with overall trend, position distribution, key highlights (wins/concerns/opportunities), detailed analysis, SERP feature report, GEO visibility, competitive position, recommendations.
Reference: See references/ranking-analysis-templates.md for complete output templates for all 7 steps.
Validation Checkpoints
Input Validation
- Keywords list is complete with search volumes
- Target domain and tracking location are specified
- Competitor domains identified for comparison
- Historical baseline data available or initial tracking period set
Output Validation
- Every metric cites its data source and collection date
- Ranking changes include context (vs. previous period)
- Significant movements have explanations or investigation notes
- Source of each data point clearly stated (~~SEO tool data, ~~search console data, user-provided, or estimated)
Example
User: "Analyze my ranking changes for the past month"
Output:
# Ranking Analysis: [current month, year]
## Summary
Your average position improved from 15.3 to 12.8 (-2.5 positions = better)
Keywords in top 10 increased from 12 to 17 (+5)
## Biggest Wins
| Keyword | Old | New | Change | Possible Cause |
|---------|-----|-----|--------|----------------|
| email marketing tips | 18 | 5 | +13 | Likely driven by content refresh |
| best crm software | 24 | 11 | +13 | Correlates with new backlinks acquired |
| sales automation | 15 | 7 | +8 | Correlates with schema markup addition |
## Needs Attention
| Keyword | Old | New | Change | Action |
|---------|-----|-----|--------|--------|
| marketing automation | 4 | 12 | -8 | Likely displaced by new HubSpot guide |
**Recommended**: Update your marketing automation guide with [current year] statistics and examples.
Tips for Success
- Track consistently - Same time, same device, same location
- Include enough keywords - 50-200 for meaningful data
- Segment by intent - Track brand, commercial, informational separately
- Monitor competitors - Context makes your data meaningful
- Track SERP features - Position 1 without snippet may lose to position 4 with snippet
- Include GEO metrics - AI visibility increasingly important
Rank Change Quick Reference
Response Protocol
| Change | Timeframe | Action |
|---|---|---|
| Drop 1-3 positions | Wait 1-2 weeks | Monitor -- may be normal fluctuation |
| Drop 3-5 positions | Investigate within 1 week | Check for technical issues, competitor changes |
| Drop 5-10 positions | Investigate immediately | Full diagnostic: technical, content, links |
| Drop off page 1 | Emergency response | Comprehensive audit + recovery plan |
| Position gained | Document and learn | What worked? Can you replicate? |
Reference: See references/tracking-setup-guide.md for root cause taxonomy, CTR benchmarks by position, SERP feature CTR impact, algorithm update assessment, tracking configuration best practices, keyword selection and grouping strategies, and data interpretation guidelines.
Save Results
After delivering monitoring data or reports to the user, ask:
"Save these results for future sessions?"
If yes, write a dated summary to memory/monitoring/YYYY-MM-DD-<topic>.md containing:
- One-line headline finding or status change
- Top 3-5 actionable items
- Open loops or anomalies requiring follow-up
- Source data references
If any findings should influence ongoing strategy, recommend promoting key conclusions to memory/hot-cache.md.
Reference Materials
- Tracking Setup Guide — Configuration best practices, device/location settings, and SERP feature tracking setup
Next Best Skill
- Primary: alert-manager — operationalize rank changes into thresholds and follow-ups.
How to use rank-tracker on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add rank-tracker
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches rank-tracker from GitHub repository aaron-he-zhu/seo-geo-claude-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate rank-tracker. Access the skill through slash commands (e.g., /rank-tracker) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★39 reviews- ★★★★★Olivia Brown· Dec 24, 2024
We added rank-tracker from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Fatima Okafor· Dec 16, 2024
Useful defaults in rank-tracker — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Kaira Martin· Dec 8, 2024
rank-tracker fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Fatima Haddad· Nov 27, 2024
We added rank-tracker from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Layla Choi· Nov 15, 2024
rank-tracker fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ava Sethi· Nov 7, 2024
rank-tracker is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Fatima Brown· Oct 26, 2024
rank-tracker reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Kiara Rao· Oct 18, 2024
Keeps context tight: rank-tracker is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Aisha Abebe· Oct 6, 2024
rank-tracker has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Zara Thompson· Sep 25, 2024
rank-tracker is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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