backlink-analysis▌
kostja94/marketing-skills · updated Apr 8, 2026
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Guides backlink profile analysis: assessing quality, identifying issues, and planning improvements.
SEO Off-Page: Backlink Analysis
Guides backlink profile analysis: assessing quality, identifying issues, and planning improvements.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Scope (Off-Page SEO)
- Backlink audit: Analyze profile; toxic links; competitive analysis
- Authority Score: Monitor domain/page authority; referring domains
Initial Assessment
Identify:
- Domain: Site to analyze
- Tool access: SEO tools (e.g. Ahrefs, Semrush) or free alternatives
- Goals: Audit for issues, competitive analysis, or growth planning
Key Metrics
| Metric | Meaning |
|---|---|
| Referring domains | Number of unique sites linking |
| Backlinks | Total number of links |
| Domain Rating (DR) / Domain Authority (DA) | Domain strength score |
| Anchor text distribution | Mix of branded, generic, exact match |
| Link velocity | Rate of new links over time |
Analysis Framework
1. Quality Assessment
- Relevance: Do links come from related niches?
- Authority: Are referring domains trusted?
- Context: Editorial vs. footer/sidebar links?
- Anchor text: Natural or over-optimized?
2. Risk Signals
| Signal | Action |
|---|---|
| Toxic links | Consider disavow (use cautiously) |
| Spammy anchors | Diversify anchor text naturally |
| Link schemes | Remove or disavow |
| Sudden spike | Investigate; may trigger penalty |
3. Competitive Comparison
- Compare backlink profile to competitors
- Identify link gaps (sites linking to competitors but not you)
- Find link opportunities from competitor backlinks
- See competitor-research for full methodology
Disavow File
- Use only when necessary (manual penalty, toxic links)
- Submit via Google Search Console (see google-search-console for Links report and disavow submission)
- Caution: Over-disavowing can harm; use sparingly
- References: Google Disavow
Output Format
- Profile summary: Key metrics, trends
- Quality assessment: Strengths and weaknesses
- Risk signals: Toxic or suspicious links
- Recommendations: Link building priorities, disavow if needed
- Competitive insights: Link gap opportunities
Related Skills
- google-search-console: Links report, disavow file submission
- seo-monitoring: Backlink metrics in full SEO monitoring; quality vs quantity, referral ROI
- link-building: Use analysis to plan link building
- competitor-research: Competitor backlink analysis; link gap methodology
How to use backlink-analysis 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 backlink-analysis
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches backlink-analysis from GitHub repository kostja94/marketing-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 backlink-analysis. Access the skill through slash commands (e.g., /backlink-analysis) 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.
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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
4.8★★★★★30 reviews- ★★★★★Dhruvi Jain· Dec 20, 2024
backlink-analysis reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Zaid Chen· Dec 16, 2024
backlink-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ama Ndlovu· Nov 15, 2024
We added backlink-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Oshnikdeep· Nov 11, 2024
I recommend backlink-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Ama Lopez· Nov 7, 2024
Solid pick for teams standardizing on skills: backlink-analysis is focused, and the summary matches what you get after install.
- ★★★★★Fatima Ndlovu· Oct 26, 2024
backlink-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Diya Taylor· Oct 6, 2024
backlink-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ganesh Mohane· Oct 2, 2024
Useful defaults in backlink-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Kaira Srinivasan· Sep 21, 2024
backlink-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diego Okafor· Aug 12, 2024
Keeps context tight: backlink-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
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