What does this skill do, and when should you use it?
This is the SEO/GEO survey skill for competitor research in the Aaron Marketing Skills collection. It compares domains across keywords, content, backlinks, technical SEO, AI citations, and traffic share, then produces a prioritized competitor brief. Every metric must be labeled Measured, User-provided, or Estimated, with unavailable data marked N/A. It fits teams that need evidence-based competitive intelligence and a sequenced SEO action plan.
Reads competitor URLs or domains, your site metrics, business model, target audience, industry context, and user- or tool-supplied data; distinguishes direct, indirect, and content competitors; analyzes keyword rankings, content strategy, backlinks, technical SEO, GEO/AI citations, and traffic share; benchmarks 3–5 competitors in one comparison table; ties each strength and weakness to labeled evidence; and produces an executive summary, keyword opportunities, content recommendations, and Immediate, Short-term, and Long-term plans. Optional SEO, analytics, and AI-monitoring tools may be used, along with the repository's Python Firecrawl connector for page scraping, URL mapping, and fresh-content searches.
- An SEO lead needs to benchmark 3–5 direct competitor domains and identify repeatable keyword and content wins.
- A content team entering a new market needs to understand competitor topic coverage, publishing patterns, and top-performing content.
- A GEO team wants to test which queries cite competitors and which content formats create AI-citation openings.
- A marketing lead lacks complete first-party site metrics but still wants a competitor-to-competitor benchmark with transparent limitations.
How do you install this skill?
- Confirm authorization, robots.txt, terms of service, and applicable TDM reservation signals before crawling third-party domains; Firecrawl sends target URLs and queries to a third party.
- For internal site metrics, competitor intelligence, or business-model data, confirm what may be written to memory and retain human review and recovery procedures.
- No skill-specific tests or real execution records are provided; traffic, rankings, domain age, DA/DR, and AI-citation conclusions remain subject to verification.
- Reachability of external SEO, AI-monitoring, or Firecrawl services from mainland-China networks is not established; use user-provided or first-party exports when unavailable.
- Shell / CLI
- Network access
- Local filesystem
Python 3
Install the repository in Claude Code with /plugin marketplace add aaron-he-zhu/aaron-marketing-skills, followed by /plugin install aaron-marketing@aaron; or use npx skills add aaron-he-zhu/aaron-marketing-skills on a compatible Agent Skills host. You may also clone it with git clone https://github.com/aaron-he-zhu/aaron-marketing-skills. The source does not document a separate installation procedure for this individual skill.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/seo-geo/survey/competitor-analysis" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Use Analyze SEO strategy for [competitor URL] or Compare my site [URL] against [competitor 1], [competitor 2], [competitor 3]. If no competitors are named or inferable, the skill asks for 2–5 competitors or offers to infer them through serp-analysis first. Without tools, provide competitor URLs, your site metrics, and industry context.
What are this skill's strengths and limitations?
- Covers keyword, content, backlink, technical SEO, AI-citation, and traffic-share dimensions in one workflow.
- Requires explicit Measured, User-provided, and Estimated labels, reducing the risk of presenting inference as fact.
- Defines a concrete quality bar: a 3–5 competitor comparison table, evidence-backed strengths and weaknesses, and staged recommendations.
- Can work from pasted data without optional tools and supports the repository's Python zero-dependency fetch connector.
- A useful analysis depends on competitor URLs, site metrics, and industry context; the skill stops when a competitor set cannot be established.
- Without tools or supplied data, required metrics such as traffic share or domain authority may be Estimated or N/A.
- The source provides no standalone test results, performance figures, or cross-host validation report for this skill.
- A pairwise topic-coverage gap map is outside its primary scope and should be handed to content-gap-analysis.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Competitor SEO & GEO Analyst this page | 51 · Use with care | ★ 3k | 12d ago | Apache-2.0 |
| Blog Brief Planner | 44 · Not recommended | ★ 2.4k | 13d ago | MIT |
| Off-Site & AI Referral Analyzer | 59 · Recommended | ★ 3k | 12d ago | Apache-2.0 |
| Content Gap Analysis | 52 · Use with care | ★ 3k | 12d ago | Apache-2.0 |
| Competitor Comparison Page Builder | 47 · Use with care | ★ 19k | 22d ago | MIT |
The source defines a clear boundary with content-gap-analysis: this skill handles broader competitive intelligence and SEO/GEO benchmarking, while content-gap-analysis handles a pairwise map of topics a competitor has that your site lacks.
How did FollowSkills review this skill?
The evidence shows least-privilege tendencies: optional tools, robots.txt preflight, a third-party Firecrawl egress notice, estimate labeling, and N/A handling. However, the skill writes and promotes findings into memory without explicit per-write user confirmation, and it does not fully specify sensitive business-data handling or rollback, so points are deducted. No red-line risk is evident; the unverified publisher is unknown and is not penalized by itself.
The contract, stop/continue gates, metric labels, and N/A failure rule are coherent, with templates for the main workflow. Static review cannot reproduce the key path, and external-tool availability, parameter behavior, abnormal-input feedback, and host-specific execution are not sufficiently verified by this skill, so the score remains below the static ceiling of 10.
Triggers, audience, inputs, outputs, the non-fit boundary for topic-coverage gap maps, and next-skill routing are clear, with a manual no-tool fallback. Environment constraints, depth of Chinese-language support, and mainland-China reachability are not verified, while the enhanced path depends on external fetching, so points are deducted.
The skill has strong information architecture, Quick Start, contract, data sources, instructions, templates, examples, limitations, version, Apache-2.0 licensing, and quarterly maintenance guidance. It lacks a clearly named maintainer, changelog, and skill-specific update path; the data-source section also contains formatting anomalies such as duplicated ~~ markers.
The intended output is concrete: a comparison table, evidence-backed strengths and weaknesses, and Immediate/Short-term/Long-term actions. However, completion depends on user-supplied data or external tools, and required metrics such as traffic share, rankings, and backlinks may remain estimates; static review cannot verify representative output, so the score is capped at 7.
The skill requires Measured/User-provided/Estimated labels and evidence-linked findings tied to named competitors and metrics, providing useful auditability. The included example contains unsourced marketing assertions, and this path has no dedicated tests or third-party execution evidence, so it receives less than the static maximum.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →