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seo-ahrefs-content-gap

Find keywords that competitors rank for but the target domain does not, using Ahrefs data. Reveals content opportunities and topic gaps. Use when user says "content gap", "keywords competitors rank for", "missing keywords", "competitor keywords", or "content gap analysis".

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Ahrefs Content Gap Analysis

Discovers keywords competitors rank for that the target domain does not, revealing content opportunities. Uses runtime schema discovery to choose the best available Ahrefs tool.

References

@skills/seo/references/mcp-degradation.md @skills/seo/references/ahrefs-api-reference.md

Inputs

  • domain: The bare target domain to analyze (e.g., example.com). Strip https://, http://, and trailing slashes.
  • competitors (optional): Up to 3 competitor domains, space-separated (e.g., competitor1.com competitor2.com). If not provided, auto-detect using Ahrefs organic competitors tool.

MCP Check

Before proceeding, verify Ahrefs MCP is available:

  1. Use ToolSearch with query +ahrefs
  2. If tools are returned → Ahrefs MCP is available, proceed to Execution
  3. If no tools returned → display the Ahrefs MCP error template from references/mcp-degradation.md and stop

Execution

Step 1 — Identify Competitors

If competitors parameter provided: use those domains directly.

If no competitors specified:

  • Call mcp__claude_ai_ahrefs__site-explorer-organic-competitors with target: the bare domain
  • Select top 3 competitors by common keyword overlap from the response

Step 2 — Runtime Schema Discovery for Content Gap Tool

IMPORTANT: The filter parameter for keywords-explorer-matching-terms that enables competitor-domain filtering is UNVERIFIED. Discover the schema at runtime:

  1. Use ToolSearch to load mcp__claude_ai_ahrefs__keywords-explorer-matching-terms
  2. Inspect the tool's parameter schema carefully
  3. Decision:
    • If the tool has a competitor/domain filter parameter → proceed with Approach A (direct filter)
    • If the tool has no such filter → fall back to Approach B (cross-reference)

Document which approach was used in the output.

Step 3A — Direct Filter Approach (if schema supports it)

For each competitor domain identified:

  • Call mcp__claude_ai_ahrefs__keywords-explorer-matching-terms with:
    • target: the competitor domain keyword or filter parameter (per discovered schema)
    • Apply any discovered competitor/domain filter to find keywords competitor ranks for
  • Cross-reference against target domain's keywords to identify gaps

Step 3B — Cross-Reference Approach (fallback)

  1. Call mcp__claude_ai_ahrefs__site-explorer-organic-keywords with target: the target domain → collect target's keyword set

  2. For each of the 3 competitor domains:

    • Call mcp__claude_ai_ahrefs__site-explorer-organic-keywords with target: the competitor domain
    • Collect their keyword set
  3. Find keywords in competitor sets NOT in target's keyword set → these are gaps

Step 4 — CRITICAL: Monetary Conversion

cpc is returned in CENTS. Divide by 100 before display. Format as USD per click: $X.XX.

Example: API returns cpc = 350 → display as $3.50/click

Step 5 — Prioritize Gaps

Sort content gap keywords by:

  1. Volume descending (highest search demand first)
  2. Filter out keywords with position >50 for the target domain (focus on true gaps)

Output Format

## Ahrefs Content Gap Analysis: example.com

**Method used:** [Approach A — direct filter] or [Approach B — cross-reference]
**Competitors analyzed:** competitor1.com, competitor2.com, competitor3.com

### Content Gap Opportunities

| Keyword | Volume | Difficulty | CPC | Competitor Ranking | Your Position |
|---------|--------|-----------|-----|-------------------|---------------|
| seo checklist | 8,100 | 42 | $3.20/click | competitor1.com #3 | Not ranking |
| on-page seo guide | 5,400 | 38 | $2.80/click | competitor2.com #5 | Not ranking |
| technical seo audit | 3,600 | 55 | $5.10/click | competitor1.com #2 | Not ranking |

### Summary
- **Total gap keywords found:** 340
- **High-opportunity gaps** (volume >1,000, difficulty <50): 45 keywords
- **Top content opportunity:** Create comprehensive "seo checklist" guide targeting
  the cluster around "seo checklist", "seo audit checklist", "on-page seo checklist"

Error — Ahrefs MCP Not Available

If MCP check fails, display the Ahrefs error template from references/mcp-degradation.md:

## Ahrefs MCP Not Available

The `/seo ahrefs content-gap` command requires the Ahrefs MCP, which is not
currently connected.

**What you can do:**
- Use `/seo audit <url>` for a full static SEO analysis without live Ahrefs data
- Use `/seo technical <url>` for technical SEO issues without backlink/keyword data

**To connect Ahrefs MCP:**
- Ensure the Ahrefs MCP is registered at user scope in ~/.claude/mcp.json
- Verify with: cat ~/.claude/mcp.json | grep -i ahrefs
- Ahrefs MCP must be registered at user scope (not project scope) to work in subagents

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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Comprehensive SEO analysis for any website or business type. Orchestrates 52 sub-skills (52 active): full site audits, technical SEO (CWV/INP), schema, E-E-A-T content quality, images, sitemaps, GEO for AI Overviews, llms.txt generation, AI crawler audit, plus live GSC and Ahrefs MCP data. GSC: overview, drops, opportunities, brand-vs-nonbrand, cannibalization, compare, content-decay, index-issues, new-keywords. Ahrefs: overview, backlinks, keywords, competitors, content-gap, broken-links, new-links, anchor-analysis, dr-history, top-pages. Cross-MCP: serp, content-brief, brand-radar, site-audit-pro, report. Local: log-analysis, ai-content-check, internal-links, local, migration-check, obsidian-kb. AI Readability: llms-txt, robots-ai. Performance: lighthouse-audit, core-web-vitals, page-experience. Quality & AI Search: rich-results, ai-optimization, eeat-audit, helpful-content. Triggers on: "SEO", "audit", "schema", "Core Web Vitals", "sitemap", "E-E-A-T", "AI Overviews", "GEO", "technical SEO", "content quality", "structured data", "GSC", "Ahrefs", "backlinks", "keywords", "search console", "domain rating", "local SEO", "migration", "lighthouse", "pagespeed", "LCP", "INP", "CLS", "page experience", "interstitials", "mobile friendly", "rich results", "rich snippets", "schema eligibility", "AI optimization", "AI search readiness", "EEAT", "trust signals", "helpful content", "people-first", "content quality gate".

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