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Agent skill

SEO Competitor Gap Analysis

by seranking in seranking/seo-skills

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.

MITAuto-check passedMarketing & SEO

Install SEO Competitor Gap Analysis

skills CLI
$ npx skills add seranking/seo-skills --skill seo-competitor-gap-analysis -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install seranking/seo-skills seo-competitor-gap-analysis --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/seranking/seo-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/seo-competitor-gap-analysis .claude/skills/seo-competitor-gap-analysis && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-competitor-gap-analysis
GitHub stars
160
Token cost
~1.6k tokens
SKILL.md length
510 words
Files
1
Skills in repo
32
Repo updated
First seen
Licence
MIT

At a glance

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.

  • Works in 7 steps: Validate or discover competitors… → Pull competitor keyword sets… → Pull target keyword set… → …
  • The user asks for a competitor gap analysis
  • SKILL.md covers Prerequisites, Process, Output format and Tips
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

SEO Competitor Gap Analysis is an agent skill from seranking/seo-skills. 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.

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Keyword research. The repository describes itself as: Claude SEO Skills — production Claude Agent Skills for the SE Ranking MCP server. Content briefs, AI Search share of voice, audits, backlink gaps, keyword clusters, schema… The licence is MIT.

When your agent uses it

  • The user asks for a competitor gap analysis
  • Organic content gap
  • Missing keyword opportunities
  • Wants to see what their competitors are ranking for that they are not

Example prompts

  • “/seo-competitor-gap-analysis”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Validate or discover competitors DATA_getDomainCompetitors
  2. Pull competitor keyword sets DATA_getDomainKeywords
  3. Pull target keyword set DATA_getDomainKeywords
  4. Compute the gap DATA_getDomainKeywordsComparison (cross-check)
  5. Filter and segment
  6. Score and prioritise
  7. Map to content actions

What it can do on your machine

Read from SKILL.md and the folder at commit fd6d140. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO Competitor Gap Analysis loads about 1.6k tokens when it runs. Until then it costs about 98 tokens; SKILL.md has 510 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~98
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from seranking/seo-skills at commit fd6d140, republished under its MIT licence (© seranking). 510 words, ~1,568 tokens.

Download SKILL.mdSave it as .claude/skills/seo-competitor-gap-analysis/SKILL.md (or your agent's skills folder).
name
seo-competitor-gap-analysis
description
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.

Example output: 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

  • SE Ranking 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 DATA_getDomainCompetitors

    • 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: the upstream API does not support limit/offset, so this call returns the full set (~60KB for popular domains) and the MCP harness writes it to a file. Read that file path, parse the {data: [...]} JSON, sort by common_keywords desc, and take the top 5.

  2. Pull competitor keyword sets DATA_getDomainKeywords

    • For each competitor, pull keywords where they rank in the top 20 of the target country.
    • Save per-competitor lists.

  3. Pull target keyword set DATA_getDomainKeywords

    • For the target domain, pull all ranking keywords in the target country (any position).
    • This is the exclusion set.

  4. Compute the gap DATA_getDomainKeywordsComparison (cross-check)

    • Keywords ranked by at least one competitor in the top 20 but not ranked by the target domain at all.
    • Use the comparison endpoint as a cross-check.

  5. 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.

  6. 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.

  7. 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).
Show full SKILL.md (178 more words)Show less

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:

markdown
# 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 DT, 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. Add the gap keywords to an SE Ranking project for rank tracking once content ships.

## 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

  • Data API rate limit: 10 requests per second. For large sites, DATA_getDomainKeywords may paginate heavily; set a ceiling (e.g., top 1,000 keywords per domain) unless the user explicitly asks for the full set.
  • Call DATA_getCreditBalance before running. A full pass on 10 seeds typically consumes 30–80 credits; 20 seeds can exceed 150.
  • 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.

© seranking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/seo-competitor-gap-analysis of seranking/seo-skills.

Open the folder on GitHubat commit fd6d140

Compare with similar skills

SEO Competitor Gap Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

SEO Competitor Gap Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
SEO Competitor Gap Analysis this skillseranking/seo-skills160—~1.6kAutomated safety check: PassMIT
SEO Keyword ClusteringAgriciDaniel/claude-seo18k2 repos~3.3kAutomated safety check: PassMIT
Evaluate Skillevery-app/open-seo23k—~1.8kAutomated safety check: NotesMIT
SEO Content Brief GeneratorAgriciDaniel/claude-seo18k2 repos~2.6kAutomated safety check: PassMIT
Blog GoogleAgriciDaniel/claude-blog2.3k1 repos~3.3kAutomated safety check: NotesMIT
FLOW SEO FrameworkAgriciDaniel/claude-seo18k2 repos~1.4kAutomated safety check: PassMIT

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Categories

Questions about SEO Competitor Gap Analysis

What does SEO Competitor Gap Analysis do?

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. SEO Competitor Gap Analysis is an agent skill from seranking/seo-skills. 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.

When should I use SEO Competitor Gap Analysis?

SEO Competitor Gap Analysis fits situations like: the user asks for a competitor gap analysis; organic content gap; missing keyword opportunities; wants to see what their competitors are ranking for that they are not.

How do I install SEO Competitor Gap Analysis in Claude Code?

Run `npx skills add seranking/seo-skills --skill seo-competitor-gap-analysis -a claude-code`. Or copy the skill folder (skills/seo-competitor-gap-analysis in seranking/seo-skills) into .claude/skills/seo-competitor-gap-analysis in your project. Claude Code loads it when a task matches its description.

How do I install SEO Competitor Gap Analysis in Codex?

Run `npx skills add seranking/seo-skills --skill seo-competitor-gap-analysis -a codex`. Or copy the skill folder (skills/seo-competitor-gap-analysis in seranking/seo-skills) into .agents/skills/seo-competitor-gap-analysis in your project. Codex loads it when a task matches its description.

Can I use SEO Competitor Gap Analysis in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seranking/seo-skills --skill seo-competitor-gap-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-competitor-gap-analysis, .gemini/skills/seo-competitor-gap-analysis, .github/skills/seo-competitor-gap-analysis and .opencode/skills/seo-competitor-gap-analysis in your project.

What does SEO Competitor Gap Analysis need to run?

SKILL.md names no scripts, command-line tools or credentials: SEO Competitor Gap Analysis is instructions for the agent only.

Does SEO Competitor Gap Analysis access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is SEO Competitor Gap Analysis safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO Competitor Gap Analysis use?

SEO Competitor Gap Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO Competitor Gap Analysis use?

About 1.6k tokens (SKILL.md is roughly 6.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to SEO Competitor Gap Analysis?

Skills that share tags, products or a category with SEO Competitor Gap Analysis: SEO Keyword Clustering (AgriciDaniel/claude-seo, 18k stars), Evaluate Skill (every-app/open-seo, 23k stars), SEO Content Brief Generator (AgriciDaniel/claude-seo, 18k stars) and Blog Google (AgriciDaniel/claude-blog, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO Competitor Gap Analysis?

seranking (a GitHub organization) maintains it in seranking/seo-skills, which has 160 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on June 25, 2026.

Source: seranking/seo-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.