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Seo Competitor Gap Analysis

skill-amirjahfar1-automate-seo-with-claude-seo-competitor-gap-analysis · by amirjahfar1

Compare a target domain to its top organic competitors and surface keywords the competitors rank for that the target does not, filtered by intent, volume, and difficulty. Use when the user asks for a competitor gap analysis, keyword gap, organic content gap, missing keyword opportunities, or wants to see what their competitors are ranking for that they are not.

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Install

$ agentstack add skill-amirjahfar1-automate-seo-with-claude-seo-competitor-gap-analysis

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

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✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

> Example output: [examples/seo-competitor-gap-analysis-wix-com-20260514/REPORT.md](../../examples/seo-competitor-gap-analysis-wix-com-20260514/REPORT.md)

Competitor Gap Analysis

Identify the specific keywords your competitors rank for in the top 20 that your domain does not, ranked by commercial value and realistic capture difficulty.

Prerequisites

  • DataForSEO MCP server connected.
  • User provides: (a) target domain, (b) 3 to 5 competitor domains (or ask the skill to auto-discover them), (c) market country (default: us), and optionally filters (min volume, max KD, intent).

Process

  1. Validate or discover competitors mcp__dataforseo__dataforseo_labs_google_competitors_domain
  • If the user did not provide competitors, pull the top 5 organic competitors for the target in the target market.
  • Surface the list to the user and ask them to confirm or override before proceeding.
  • Note: large competitor lists can exceed the MCP inline limit. Cap with limit and filters; if the result is written to a file, read that path, parse the {data: [...]} JSON, sort by common_keywords desc, and take the top 5.
  1. Pull competitor keyword sets mcp__dataforseo__dataforseo_labs_google_ranked_keywords
  • For each competitor, pull keywords where they rank in the top 20 of the target country.
  • Save per-competitor lists.
  1. Pull target keyword set mcp__dataforseo__dataforseo_labs_google_ranked_keywords
  • For the target domain, pull all ranking keywords in the target country (any position).
  • This is the exclusion set.
  1. Compute the gap mcp__dataforseo__dataforseo_labs_google_domain_intersection (cross-check)
  • Keywords ranked by at least one competitor in the top 20 but not ranked by the target domain at all.
  • Use the domain-intersection endpoint as a cross-check.
  1. Filter and segment
  • Apply user-specified filters on volume, KD, and intent.
  • Segment by intent: informational, commercial, transactional, navigational.
  • Segment by competition: how many of the N competitors rank for each gap keyword.
  1. Score and prioritise
  • Score each gap keyword: traffic potential (volume × CTR model) + intent weighting + inverse KD.
  • Surface the top 50 opportunities with reasoning per keyword.
  1. Map to content actions
  • For each top opportunity, recommend: new article, expand existing page, refresh existing page, programmatic template.
  • Flag quick wins: competitors rank with thin content (detected by URL pattern and content-length heuristics).

Output format

Create a folder seo-competitor-gap-analysis-{target-slug}-{YYYYMMDD}/ with:

seo-competitor-gap-analysis-{target-slug}-{YYYYMMDD}/
├── REPORT.md                                (synthesised report — primary deliverable)
├── gaps.csv                                 (full gap list — load-bearing CSV the writers/planners paste into briefs)
└── evidence/
    ├── 01-competitors.md                    (competitor list / discovery — raw step output)
    ├── 02-competitor-keywords-{domain}.md   (one per competitor — raw step output)
    ├── 03-target-keywords.md                (target's existing ranking set — raw step output)
    └── 04-gap-raw.md                        (human-readable full gap list before filtering — raw step output)

Top-level: REPORT.md + gaps.csv. The numbered step files preserve the raw API outputs in evidence/ for reproducibility.

REPORT.md follows this shape:

# Competitor Gap: {target}
Market: {country}
Competitors analysed: {list}

## Summary
- Competitor keywords in top 20: {n}
- Target keywords overall: {n}
- Gap keywords (opportunities): {n}
- Gap traffic potential: ~{n}/mo

## Top 50 opportunities

### Informational intent
| # | Keyword | Volume | KD | Competitors ranking | Action | Score |
|---|---|---|---|---|---|---|
| 1 | {kw} | {n} | {n} | {3 of 5} | New article | {score} |
| 2 | ... | ... | ... | ... | ... | ... |

### Commercial intent
| # | Keyword | Volume | KD | Competitors ranking | Action | Score |
|---|---|---|---|---|---|---|
...

### Transactional intent
...

## Quick wins (top 10)
Keywords where competitors rank in positions 5 to 20 with thin content, low domain rank, or old dates.

| # | Keyword | Weakest competitor position | Suggested angle |
|---|---|---|---|
| 1 | {kw} | example.com at #14 (2022 article, 800 words) | Fresh, comprehensive guide |

## Recommended next steps
1. Run `content-brief` on the top 3 opportunities to generate writer-ready briefs.
2. Run `keyword-cluster-planner` on the full gap list to build a sequencing plan.
3. Track the gap keywords once content ships — for your own verified site use GSC (`mcp__gscServer__get_search_analytics`); for any-domain tracking, save dated `serp_organic_live_advanced` snapshots to local storage (the `seo-drift` pattern).

## Files
- gaps.csv: full gap list for spreadsheet analysis
- evidence/04-gap-raw.md: human-readable full gap list before filtering

gaps.csv columns: keyword,volume,kd,cpc,intent,competitors_ranking,top_competitor_position,target_position,action,score

Tips

  • DataForSEO allows up to 2,000 calls/min, 30 concurrent. Skills pace sequentially. For large sites, dataforseo_labs_google_ranked_keywords may paginate heavily; set a ceiling (e.g., top 1,000 keywords per domain via limit) unless the user explicitly asks for the full set.
  • DataForSEO bills per call; this run issues ~N calls (one ranked-keywords pull per seed plus the intersection cross-checks). Use the documented limit/ceiling params to cap.
  • The competitors_ranking count is the best signal of realism. Keywords ranked by 4 of 5 competitors are validated opportunities; keywords ranked by only 1 may be noise.
  • Do not recommend capturing branded competitor keywords unless the user explicitly asks. Pivoting to compete on "competitor brand review" is a viable strategy but only if the user opts in.
  • When many gap keywords cluster around a theme, recommend a hub page plus cluster rather than 50 individual articles.
  • Chain this skill with content-brief and keyword-cluster-planner naturally. Mention them in the Recommended next steps section of the output.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.