fix-linking▌
calm-north/seojuice-skills · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Design and audit internal link structures using hub-and-spoke topology, PageRank flow, and anchor text optimization.
- ›Supports five architecture models (hub-and-spoke, silo, flat, pyramid, mesh) with guidance on which fits different site sizes and content types
- ›Includes orphan page detection, link depth analysis, and anchor text diversity assessment to identify ranking barriers
- ›Provides concrete link injection plans with source pages, target pages, anchor text suggestions, and priorit
Fix Linking
Design and audit internal link structures using hub-and-spoke topology, PageRank flow logic, and anchor text budgets.
Why Internal Links Matter
Internal links do two things: (1) pass PageRank between pages, and (2) signal topical relevance via anchor text. A page with zero incoming internal links is an orphan — invisible to authority flow regardless of content quality.
Architecture Model Selection
Before auditing links, choose the right architecture model for the site:
| Model | Best For | Site Size | Key Characteristic |
|---|---|---|---|
| Hub-and-Spoke (Topic Cluster) | Content marketing, SaaS, publishers | 50-500 pages | Bidirectional links between pillar and cluster articles |
| Silo Structure | E-commerce, directories, large enterprises | 100+ categories | Vertical-only links within topic silos |
| Flat Architecture | Small sites, portfolios, startups | <100 pages | All pages within 2-3 clicks, cross-linked freely |
| Pyramid | News sites, large blogs, corporate | 500+ pages | Top-down hierarchy, authority concentrates at top |
| Mesh/Matrix | Knowledge bases, wikis, help centers | Any | Free-form linking between any related pages |
Key Metrics by Architecture
| Metric | Hub-and-Spoke | Silo | Flat | Pyramid | Mesh |
|---|---|---|---|---|---|
| Target click depth | ≤3 | ≤4 | ≤2 | ≤4 | ≤3 |
| Internal links per page | 5-10 | 3-7 | 8-15 | 3-5 | 8-15 |
| Cross-section links | Many | Few | N/A | Some | Many |
| Authority distribution | Distributed to hubs | Top of silo | Even | Top-heavy | Even |
Expected ROI from Architecture Changes
| Change | Typical Impact | Timeline |
|---|---|---|
| Fix orphan pages | +15-30% traffic to those pages | 2-4 weeks |
| Build first topic cluster | +10-25% traffic to cluster pages | 4-8 weeks |
| Reduce click depth by 1 level | +5-15% crawl efficiency | 2-6 weeks |
| Anchor text optimization | +5-10% ranking improvement | 4-12 weeks |
| Full architecture migration | +20-50% overall organic traffic | 3-6 months |
Recommended for most sites: Hub-and-Spoke as the primary model, with silo-style isolation between unrelated topic areas.
Phase 1: Map the Current Structure
Before designing links, understand what exists:
- Hub pages. Pages that aggregate links and distribute authority — homepage, category pages, pillar articles. List them.
- Orphan pages. No incoming internal links from crawlable pages. They receive zero PageRank from the internal graph.
- Link depth. How many clicks from the homepage does each important page require? Depth 4+ pages are effectively buried.
- Anchor text. Repeated identical anchors are fine. Generic anchors ("click here", "read more") waste relevance signal.
Ask the user for their page list or sitemap, or work with what they describe.
Phase 2: Hub-and-Spoke Design
Hub Pages (pillar/category)
- Linked from homepage or main navigation
- Link out to all supporting pages in their cluster
- Serve as authority redistribution nodes
Spoke Pages (supporting/cluster articles)
- Receive at least 2-3 internal links from hub and sibling spokes
- Always link back to their hub page
- Link to 2-4 sibling spokes where contextually relevant
- Never link to competing pages (same keyword intent)
Cross-Cluster Links
- Only when there is genuine topical relevance
- Use to signal E-E-A-T connections (e.g., case study → methodology page)
- Limit to 1-2 per page to avoid diluting cluster coherence
Phase 3: Anchor Text Budget
For internal links, each page should receive anchor text in this distribution:
| Anchor Type | Target Share | Example |
|---|---|---|
| Exact match | 20-30% | "content decay detection" |
| Partial match | 30-40% | "detecting when content decays" |
| Related/semantic | 20-30% | "pages losing traffic" |
| Branded | 5-10% | "our decay detection feature" |
| Generic | 0-5% | "learn more" |
Diversity improves relevance coverage for semantic search.
Phase 4: Orphan Page Resolution
For each orphan page, apply this decision tree:
- Worth ranking? If no (thin, superseded), redirect to the closest relevant page. Stop.
- Which cluster? Find the nearest hub page.
- Which 2-3 existing pages would readers logically arrive from? These are injection points.
- What anchor text fits naturally? Match the orphan page's target keyword.
- Does the hub page need a content update to include a contextual reference?
Phase 5: Link Injection Plan
Produce a concrete action plan:
| Source Page | Target Page | Suggested Anchor Text | Where on Source Page | Priority |
|---|---|---|---|---|
| /blog/seo-guide | /tools/keyword-research | "keyword research tool" | Under "Research Phase" heading | high |
| ... | ... | ... | ... | ... |
Priority = high if the target is a revenue-critical or high-intent page.
Output Format
Internal Link Audit: [domain]
Current State
- Orphan pages: [count or list]
- Average link depth for important pages: [value]
- Hub pages identified: [list]
- Anchor text diversity: [assessment]
Hub-and-Spoke Map For each cluster: Hub → [Spoke 1, Spoke 2, Spoke 3 ...]
Link Injection Plan [Table from Phase 5]
Anchor Text Fixes Pages where anchor text is entirely generic and needs replacement.
Recommendations
- Orphan pages that are revenue-critical — link them first
- Pages at depth 4+ that should be at depth 2 — add shortcuts via hub pages
- Clusters with weak internal connectivity — add sibling cross-links
- Pages with 0-1 incoming links that are important for conversions
Pro Tip: Try the free Internal Link Finder and Anchor Text Diversity tools at seojuice.com. SEOJuice MCP users can run
/seojuice:site-healthfor instant orphan page detection, link depth distribution, and most-linked pages — theget_site_topologytool maps your entire internal link graph automatically.
How to use fix-linking 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 fix-linking
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches fix-linking from GitHub repository calm-north/seojuice-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 fix-linking. Access the skill through slash commands (e.g., /fix-linking) 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★★★★★35 reviews- ★★★★★Aditi Singh· Dec 28, 2024
fix-linking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Emma Kim· Dec 24, 2024
I recommend fix-linking for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Zara Khan· Dec 20, 2024
We added fix-linking from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Chaitanya Patil· Dec 4, 2024
fix-linking is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Piyush G· Nov 23, 2024
fix-linking fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Aisha Garcia· Nov 19, 2024
fix-linking is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Emma White· Nov 15, 2024
Useful defaults in fix-linking — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Shikha Mishra· Oct 14, 2024
fix-linking has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aisha Johnson· Oct 10, 2024
Solid pick for teams standardizing on skills: fix-linking is focused, and the summary matches what you get after install.
- ★★★★★Zara Harris· Oct 6, 2024
Registry listing for fix-linking matched our evaluation — installs cleanly and behaves as described in the markdown.
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