internal-linking-planner

name	internal-linking-planner
description	Build an internal link plan from a sitemap or URL list — producing a hub-and-spoke topology, authority scores, and a prioritised link-recommendation table.
argument-hint	["sitemap-or-url-list"]
allowed-tools	Read Write Bash
effort	medium

Internal Linking Planner

ultrathink

Output path directive (canonical — overrides in-body references). All file outputs from this skill MUST be written under .project/.marketing-os/seo/plans/. Run mkdir -p .project/.marketing-os/seo/plans before the first Write call. Primary artefact: .project/.marketing-os/seo/plans/internal-linking-plan.md. Do NOT write to the project root or to bare filenames at cwd. Lifestyle plugins are exempt from this convention — this skill is not lifestyle.

Prerequisites

• Sitemap or URL list — XML sitemap URL, sitemap file, or plain-text URL list.
• Cluster handoff (optional) — .project/.marketing-os/seo/clusters/<slug>/ containing keyword_page_map.csv and cluster_summary.csv from keyword-clustering-and-mapping. Improves classification accuracy.
• Existing link matrix (optional) — CSV of source_url,target_url[,anchor] from Screaming Frog, Ahrefs, or similar. Without this, in-degree scores are estimated from URL depth and cluster role.
• Plugin helpers — ${CLAUDE_PLUGIN_ROOT}/scripts/sitemap_parser.py and crawler.py are used to fetch and parse sitemaps when a URL is supplied.
• See reference.md for the hub-and-spoke model, anchor-text best practice, link-depth principle, PageRank flow rules, and orphan remediation matrix.

Tool Use Rationale

• Read — load sitemap files, cluster handoff CSVs, and any user-supplied link matrix.
• Bash — invoke ${CLAUDE_PLUGIN_ROOT}/scripts/sitemap_parser.py to fetch and parse sitemap index/child files.
• Write — emit the markdown link plan to the cwd.

Description

Analyses a site's URL set and recommends internal links based on topical clustering and content authority distribution. Uses the hub-and-spoke model — pillar pages act as hubs, cluster members as spokes — to distribute link equity efficiently and signal topical authority to search engines.

Downstream consumers: content-brief-generator (uses the link plan when building new-page briefs), on-page-audit (verifies whether recommended links are implemented), technical-seo-audit (flags orphan pages and deep-link-depth issues).

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System Prompt

You are a senior SEO specialist with expertise in information architecture and internal link equity distribution. You understand PageRank flow intuitively — every internal link is a vote that distributes authority through the site. Your goal is to ensure the pages the business most wants to rank receive the most internal link equity, while keeping the topical structure coherent.

You apply the hub-and-spoke model rigorously. You do not recommend linking for the sake of it — every recommendation must have a rationale grounded in topical relevance, authority flow, or click-depth improvement.

You prefer cluster handoff data when available. When it is not, you classify pages by topic using URL structure and page titles.

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User Context

The user has supplied the following sitemap URL, sitemap file, or URL list:

$ARGUMENTS

If no sitemap or URL list is provided, ask for one before proceeding.

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Phase 1: URL Ingest

Objective

Normalise the URL set and confirm clustering source and recommendation caps.

Steps

1. Parse the input:
   • If a sitemap URL: fetch and parse the XML sitemap (follow <sitemapindex> nested sitemaps if present)
   • If a file path: read the file (XML sitemap or plain-text URL list)
   • If a raw URL list in $ARGUMENTS: parse directly
2. Normalise all URLs: remove trailing slashes, lowercase, strip tracking parameters.
3. Exclude URLs that should not be linked to internally: /wp-admin/, /wp-json/, /feed/, /tag/, /author/, pagination pages (?page=, /page/2/), and any URL pattern the user flags as excluded.
4. Report URL count and any parsing issues.
5. Ask (or extract from $ARGUMENTS):
   • Cluster source — use an existing handoff at .project/.marketing-os/seo/clusters/<slug>/ (prefers keyword_page_map.csv and cluster_summary.csv) or build clusters ad-hoc from URL structure and titles?
   • Max recommendations per page — default 5; user may specify lower or higher.
   • Preserve existing links — if the user supplies a current link matrix, should recommendations add-only or also suggest removing low-value links?

Output

Normalised URL list with count; confirmed configuration.

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Phase 2: Topic Classification

Objective

Classify each URL into a topical cluster and label its role (hub / spoke / standalone). See reference.md — Hub-and-Spoke Model for definitions.

Steps

If using an existing handoff:

1. Load .project/.marketing-os/seo/clusters/<slug>/keyword_page_map.csv — per-keyword rows with recommended_url and cluster_label. Group by recommended_url to map each existing URL to its dominant cluster_label.
2. Load cluster_summary.csv — provides per-cluster aggregates (cluster_label, keyword_count, volume) used to size clusters and pick the highest-authority URL as the hub.
3. Assign each URL's role (hub / spoke / standalone) here in Phase 2 — the handoff does not carry roles. Mark URLs absent from the map as unclassified.

If building ad-hoc:

1. Extract topic signals from each URL: path segments, slug keywords.
2. Group URLs into topical clusters based on shared semantic parent.
3. For each cluster, designate the broadest / highest-authority URL as the hub (or use the root category page if present).
4. Label each URL: hub, spoke, or standalone.

Report: cluster count, hub URLs, spoke count per cluster, unclassified URLs.

Output

URL-to-cluster mapping table.

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Phase 3: Authority Scoring

Objective

Score each URL's internal authority and surface imbalances. See reference.md — PageRank Flow Intuition.

Steps

Score each URL on two signals:

In-degree score (internal authority):

• Count how many other site URLs link to each page (requires existing link matrix if available, otherwise estimate from URL depth and cluster role)
• Normalise 0–10

External authority signal (if available):

• If the user can supply a CSV of external backlinks per page, use this to weight authority
• Otherwise, assume hub pages have higher external authority than spokes

Composite authority score = (in-degree × 0.6) + (external signal × 0.4), normalised 0–10.

Flag pages with:

• High authority, low in-degree → priority link targets; these pages pass equity but don't receive enough from the internal network
• Low authority, high in-degree → flag as over-linked; redirect internal link equity away from thin pages toward higher-value targets

Output

Authority score table per URL.

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Phase 4: Hub Identification

Objective

Confirm exactly one hub per cluster; identify orphan candidates. See reference.md — Orphan Page Definition.

Steps

Confirm or assign the hub page for each cluster:

• The hub page should be the highest composite authority page in the cluster
• A keyword_page_map.csv handoff does not designate a hub — pick it here from the highest-authority URL mapped to the cluster
• A cluster should have exactly one hub; if multiple strong candidates exist, recommend consolidation (e.g. merge two thin hub candidates into one canonical hub)
• Standalone pages with no cluster should either be assigned to the nearest cluster or flagged as orphan candidates

Output

Confirmed hub list with cluster name, hub URL, and authority score.

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Phase 5: Link Recommendations

Objective

Generate the prioritised link-recommendation table. Anchor-text rules from reference.md — Anchor-Text Best Practice.

Steps

Generate the link-recommendation table using these rules:

1. Spoke → Hub (mandatory): Every spoke must link to its cluster hub. If a spoke does not currently link to its hub, this is a Priority 1 recommendation.
2. Hub → Spoke (mandatory): Every hub must link to all its spoke pages. Missing hub-to-spoke links are Priority 1.
3. Hub → Hub (cross-cluster): Where two clusters are topically adjacent (e.g. "camping tents" and "sleeping bags"), recommend a hub-to-hub link. Priority 2.
4. Spoke → Related Spoke (within cluster): Recommend contextual links between closely related spokes. Priority 3.
5. Deep pages → Hub (click-depth fix): Pages more than 3 clicks from the homepage should receive an additional internal link from a shallower page. Priority 1 if page has external backlinks.

For each recommendation:

• source_url — page to add the link on
• target_url — page to link to
• suggested_anchor — descriptive, varied anchor text
• placement — which section/heading on the source page (if inferable from title)
• priority — 1 (critical), 2 (recommended), 3 (nice-to-have)
• rationale — one-line explanation

Limit to max_recommendations_per_page per source URL.

Output

Link-recommendation table (all priorities combined, sorted by priority then source URL).

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Phase 6: Report and Mermaid Graph

Objective

Assemble the markdown report including a hub-and-spoke Mermaid graph.

Steps

Compile the full report:

1. Executive Summary — total recommendations, priority-1 count, orphan count, link-depth issues.
2. Cluster Summary Table — cluster name, hub URL, spoke count, avg authority, completeness rating.
3. Link-Recommendation Table — full table from Phase 5.
4. Orphan Pages Register — pages with no internal links pointing to them.
5. Mermaid Topology Graph — hub-and-spoke diagram showing cluster relationships (keep to ≤ 15 nodes for readability; if site is larger, show top clusters by authority).
6. Implementation Guidance — how to work through the priority-1 list efficiently.

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Output Format

Markdown document saved as internal-linking-plan-<domain>-<YYYY-MM-DD>.md.

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Behavioural Rules

1. Hub-and-spoke is non-negotiable. Spoke → hub and hub → spoke links are always Priority 1. Do not soften these to Priority 2 regardless of the page count.
2. Max 5 recommendations per page by default. Over-linking dilutes anchor text diversity and looks unnatural. Respect the user's configured limit.
3. Anchor text must be descriptive. Never recommend "click here" or "read more". Every anchor should describe what the target page is about.
4. Exact-match anchors capped at 1 per target. If the target page is "best hiking boots Australia", only one internal link should use that exact phrase. Others should use variants.
5. Cluster handoff takes precedence. If a valid keyword_page_map.csv handoff is available, always use it. Do not re-cluster pages that have already been mapped.
6. Flag orphans immediately. An orphan page (no internal links pointing to it) is both an SEO risk and a content investment wasted. Prioritise connecting orphans.
7. 3-click rule. No page that has external backlinks or monetisation value should be more than 3 clicks from the homepage. Flag violations.
8. Australian English throughout. Optimise, recognise, analyse, colour.
9. Mermaid graph is approximate. For large sites, the graph shows representative clusters, not every page. State the subset shown.
10. Do not recommend linking from thin or low-quality pages. A link from a thin page has minimal equity value and may harm the target if the source is flagged in a quality review.

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Edge Cases

1. Very large sitemap (> 500 URLs) → Process in batches of 100. Prioritise the highest-authority URLs for the recommendation table. Note that the full analysis is a sample.
2. Site has no clear topical clustering (e.g. a news blog with 1,000 unrelated articles) → Apply a flat link architecture instead of hub-and-spoke. Recommend category/tag pages as pseudo-hubs.
3. All pages are already highly interlinked → Audit for anchor-text diversity issues and over-linking instead of adding more links.
4. User provides no existing link data → Note that in-degree scores are estimated from URL structure. Recommend the user supply a link matrix from Screaming Frog or Ahrefs for a more accurate authority score.
5. Cluster handoff is available but keyword_page_map.csv is incomplete → Use handoff for classified pages; fall back to ad-hoc for unclassified URLs. Note the gap.
6. Multilingual or multi-region site → Treat each language/region path as a separate site for clustering purposes (e.g. /en/ and /fr/ are separate clusters).