Analyze the SEO of one URL, scored /80 with paste-ready fixes.

MITAuto-check passedMarketing & SEO

Install Page SEO Analysis

skills CLI
$ npx skills add indranilbanerjee/digital-marketing-pro --skill page-seo-analysis -a claude-code

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

GitHub CLI
$ gh skill install indranilbanerjee/digital-marketing-pro page-seo-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/indranilbanerjee/digital-marketing-pro.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/page-seo-analysis .claude/skills/page-seo-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
page-seo-analysis
GitHub stars
862
Used in
1 other repo
Token cost
~991 tokens
SKILL.md length
442 words
Files
1
Skills in repo
162
Repo updated
First seen
Licence
MIT

At a glance

Analyze the SEO of one URL, scored /80 with paste-ready fixes.

  • Works in 12 steps: Load brand context: Read active brand… → Fetch and parse page: Retrieve full… → Title tag analysis: Character count… → …
  • Tasks that involve SEO audit
  • SKILL.md covers Purpose, Input Required, Process and Schema Deprecation Tracking, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Page SEO Analysis is an agent skill from indranilbanerjee/digital-marketing-pro. Analyze the SEO of one URL, scored /80 with paste-ready fixes. "analyze the SEO of this page"

Its SKILL.md is about 990 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 SEO audit. The repository describes itself as: An open-source AI marketing operating system for strategy, SEO, AEO/GEO, paid media, content, CRM, and analytics - grounded in brand context, human approval, and verifiable… The licence is MIT.

When your agent uses it

  • Tasks that involve SEO audit

Example prompts

  • “analyze the SEO of this page”
  • “/page-seo-analysis”

Workflow steps

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

  1. Load brand context: Read active brand profile. Load brand guidelines if available.
  2. Fetch and parse page: Retrieve full HTML, extract all signals.
  3. Title tag analysis: Character count (50-60 chars ideal), keyword placement, brand inclusion, uniqueness, click-worthiness.
  4. Meta description analysis: Character count (150-160 chars), keyword inclusion, CTA presence, uniqueness.
  5. Heading hierarchy: H1 presence and uniqueness, H2-H6 logical structure, keyword distribution across headings.
  6. Content depth analysis: Word count, reading level, topic coverage completeness, keyword placement (primary keyword in title, intro, ≥2…
  7. E-E-A-T signals: Author byline and bio, credentials, first-hand experience indicators, citations and sources, about page link, contact…
  8. Schema markup detection: JSON-LD, Microdata, RDFa — validate against Google's supported types, check for deprecations (HowTo deprecated…
  9. Image audit: Alt text, dimensions, format, lazy loading, fetchpriority on LCP image (see image-seo-audit skill for full methodology).
  10. Internal linking: Inbound links to this page, outbound links from this page, anchor text quality, orphan page check.
  11. Technical signals: Canonical tag, robots directives, mobile viewport, HTTPS, page speed indicators, Core Web Vitals.
  12. AI search readiness: Entity consistency, citation-worthiness, structured answer formatting, concise answer blocks for featured snippets.

What it can do on your machine

Read from SKILL.md and the folder at commit 9e949f3. 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.

    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

Page SEO Analysis loads about 991 tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 442 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~28
When it runs · the whole SKILL.md, loaded when a task matches
~991

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 indranilbanerjee/digital-marketing-pro at commit 9e949f3, republished under its MIT licence (© indranilbanerjee). 442 words, ~991 tokens.

Download SKILL.mdSave it as .claude/skills/page-seo-analysis/SKILL.md (or your agent's skills folder).
name
page-seo-analysis
description
Analyze the SEO of one URL, scored /80 with paste-ready fixes. "analyze the SEO of this page"
argument-hint
[URL]
user-invocable
true

/digital-marketing-pro:page-seo-analysis

Purpose

Deep single-page SEO analysis — examines everything about one URL across all ranking dimensions. More granular than a site-wide audit. Use for landing page optimization, content refresh prioritization, or pre-publish quality checks.

Input Required

  • URL: The specific page to analyze
  • Target keyword: Primary keyword this page should rank for (optional — can be inferred)
  • Competitors: 1-3 competitor pages targeting the same keyword (optional)

Process

  1. Load brand context: Read active brand profile. Load brand guidelines if available.
  2. Fetch and parse page: Retrieve full HTML, extract all signals.
  3. Title tag analysis: Character count (50-60 chars ideal), keyword placement, brand inclusion, uniqueness, click-worthiness.
  4. Meta description analysis: Character count (150-160 chars), keyword inclusion, CTA presence, uniqueness.
  5. Heading hierarchy: H1 presence and uniqueness, H2-H6 logical structure, keyword distribution across headings.
  6. Content depth analysis: Word count, reading level, topic coverage completeness, keyword placement (primary keyword in title, intro, ≥2 H2s, conclusion, and meta — density is not a target; keyword-density percentages are a discredited metric, not a ranking factor), natural coverage of related/co-occurring terms, content freshness (last modified date).
  7. E-E-A-T signals: Author byline and bio, credentials, first-hand experience indicators, citations and sources, about page link, contact information.
  8. Schema markup detection: JSON-LD, Microdata, RDFa — validate against Google's supported types, check for deprecations (HowTo deprecated Sept 2023, FAQ restricted to gov/health Aug 2023, SpecialAnnouncement deprecated July 2025), suggest missing schema opportunities.
  9. Image audit: Alt text, dimensions, format, lazy loading, fetchpriority on LCP image (see image-seo-audit skill for full methodology).
  10. Internal linking: Inbound links to this page, outbound links from this page, anchor text quality, orphan page check.
  11. Technical signals: Canonical tag, robots directives, mobile viewport, HTTPS, page speed indicators, Core Web Vitals.
  12. AI search readiness: Entity consistency, citation-worthiness, structured answer formatting, concise answer blocks for featured snippets.
  13. Competitor comparison (if provided): Side-by-side analysis of word count, schema, headings, E-E-A-T signals vs competitor pages.
Show full SKILL.md (125 more words)Show less

Schema Deprecation Tracking

Always check and flag:

  • HowTo: Deprecated (September 2023) — rich results removed
  • FAQ: Restricted to government and health authority sites (August 2023)
  • SpecialAnnouncement: Deprecated (July 2025)
  • EnergyConsumptionDetails: Replaced by Certification schema (April 2025)

Output

Page SEO Score: XX/80
DimensionScorePriority Issues
Title & Meta/10...
Content Depth/10...
E-E-A-T/10...
Schema Markup/10...
Images/10...
Internal Links/10...
Technical/10...
AI Readiness/10...
  • Specific, actionable recommendations for each dimension
  • Exact replacement title tags and meta descriptions (with character counts)
  • Missing schema markup JSON-LD code (ready to implement)
  • Content gaps vs competitors
  • Quick wins vs strategic improvements

Agents Used

  • seo-specialist — All page-level analysis, scoring, recommendations

Scripts Used

  • tech-seo-auditor.py — Technical signal extraction
  • content-scorer.py — Content quality scoring
  • schema-generator.py — Generate missing schema markup
  • competitor-scraper.py — Competitor page comparison

© indranilbanerjee, 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/page-seo-analysis of indranilbanerjee/digital-marketing-pro.

Open the folder on GitHubat commit 9e949f3

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in indranilbanerjee/digital-marketing-pro, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Page SEO 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.

Page SEO Analysis compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Page SEO Analysis this skillindranilbanerjee/digital-marketing-pro8621 repos~991Automated safety check: PassMIT
Hreflang and International SEOAgriciDaniel/claude-seo19k5 repos~3.4kAutomated safety check: PassMIT
Google SEO APIsAgriciDaniel/claude-seo19k1 repos~4.2kAutomated safety check: PassMIT
Evaluate Skillevery-app/open-seo23k—~1.8kAutomated safety check: NotesMIT
FLOW SEO FrameworkAgriciDaniel/claude-seo19k2 repos~1.4kAutomated safety check: PassMIT
GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude11k—~2.8kAutomated safety check: NotesMIT

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Categories

Questions about Page SEO Analysis

What does Page SEO Analysis do?

Analyze the SEO of one URL, scored /80 with paste-ready fixes. Page SEO Analysis is an agent skill from indranilbanerjee/digital-marketing-pro. Analyze the SEO of one URL, scored /80 with paste-ready fixes.

When should I use Page SEO Analysis?

Page SEO Analysis fits situations like: tasks that involve SEO audit.

How do I install Page SEO Analysis in Claude Code?

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

How do I install Page SEO Analysis in Codex?

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

Can I use Page SEO 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 indranilbanerjee/digital-marketing-pro --skill page-seo-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/page-seo-analysis, .gemini/skills/page-seo-analysis, .github/skills/page-seo-analysis and .opencode/skills/page-seo-analysis in your project.

What does Page SEO Analysis need to run?

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

Does Page SEO 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 Page SEO 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 Page SEO Analysis use?

Page SEO 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 Page SEO Analysis use?

About 991 tokens (SKILL.md is roughly 4k 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 Page SEO Analysis?

Skills that share tags, products or a category with Page SEO Analysis: Hreflang and International SEO (AgriciDaniel/claude-seo, 19k stars), Google SEO APIs (AgriciDaniel/claude-seo, 19k stars), Evaluate Skill (every-app/open-seo, 23k stars) and FLOW SEO Framework (AgriciDaniel/claude-seo, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Page SEO Analysis?

indranilbanerjee (a GitHub user) maintains it in indranilbanerjee/digital-marketing-pro, which has 862 GitHub stars. The repository holds 162 skills in this directory. The repository was last updated on October 9, 2026.

Source: indranilbanerjee/digital-marketing-pro on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.