AgriciDaniel/claude-seo

claude-seo

Universal SEO skill for Claude Code. 25 sub-skills + 18 sub-agents covering technical SEO, E-E-A-T, schema, GEO/AEO, backlinks, local SEO, maps intelligence, semantic clustering, e-commerce SEO, international SEO, Google APIs, and PDF/Excel reporting. Optional DataForSEO, Firecrawl, and Banana extensions.

41/100
Stars10,003
Forks1,439
LanguagePython
LicenseMIT

Usage guide

claude-seo is an open-source project around ai-seo, claude-code, claude-code-skill with 10,003 GitHub stars. This guide focuses on when to use it, how to install it, how to run the first example, and what to verify before adopting it.

Repository license: MITCommercial use permitted, review additional terms

Key features

  • Implemented mainly in Python, useful for judging integration effort in a similar stack.
  • GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.
  • The project has a homepage, so cross-check docs, examples, and release information beyond GitHub.

Best for

  • Evaluating claude-seo for Python AI workflows.
  • Comparing a GitHub project with 10,003 stars and current repository activity.

Pros

  • claude-seo has visible GitHub traction with 10,003 stars. Topics: ai, ai-seo, claude-code.
  • The project provides an external homepage for deeper evaluation.

Cons

  • Production fit still depends on documentation depth, issue activity, and release cadence.
  • License review should confirm the MIT terms fit your use case.

Production readiness

claude-seo should be validated with its README, release history, open issues, and integration requirements before production use.

License risk

MIT is reported by GitHub; review the repository license before redistribution or commercial use.

claude-seo architecture preview

claude-seo's main path starts at the entry surface, runs through Coding agent runtime, combines Claude, Vector index / Files / repository context, GitHub, and returns User-facing result.

Entry

Web / product entry

Users start from a web UI, hosted product surface, or browser-based workflow.

https://claude-seo.md

Runtime

Coding agent runtime

The runtime reads developer intent, inspects repository context, plans edits, and returns code-oriented actions.

coding workflow

Runtime dependencies

Model

Claude

Model calls are likely routed through Claude based on README and topic signals.

Claude

Context

Vector index / Files / repository context

Context comes from Vector index, Files / repository context, which constrains what the model or runtime can use.

Vector index, Files / repository context

Tools

GitHub

Tool adapters let the runtime act outside the model through GitHub.

GitHub

Output

User-facing result

The final output is returned to the user, workflow, API caller, or downstream system.

output

Install tutorial

Before you install

  • Python runtime and an isolated virtual environment
  • A clean working directory for the first test run
1
Step 1

Check the runtime environment

claude-seo depends on a Python-style environment. Use venv, conda, or a container to keep dependencies isolated.

2
Step 2

Get the project files

Start from the official repository or package so the first run matches the documented behavior.

terminal
$ git clone --depth 1 https://github.com/AgriciDaniel/claude-seo.git
3
Step 3

Install or build dependencies

Run the next setup command detected from the project documentation.

terminal
$ curl -fsSL https://raw.githubusercontent.com/AgriciDaniel/claude-seo/main/install.sh > install.sh

Adoption guidance and sources

Practical use cases

Universal SEO skill for Claude Code. 25 sub-skills + 18 sub-agents cov

This is one of the documented reasons to evaluate claude-seo before choosing a stack.

Focus area: ai

This is one of the documented reasons to evaluate claude-seo before choosing a stack.

All project comparison

Compare claude-seo with similar projects before committing to a stack.

Before adopting

  • Complete one clean-environment verification using the official claude-seo setup path.
  • Review repository license, model weights, external services, and dependency terms for your use case.
  • Check recent commits, release cadence, issue response, and documentation depth.
  • Evaluate output quality, latency, resource usage, and recovery behavior with a small dataset.

Configuration notes

  • Review README configuration notes before using production data.

Sources checked

These links are used to verify repository, documentation, or tutorial details. Review the source pages before adopting the project.

Troubleshooting

  • If installation fails, first confirm the command is being run from the README-specified directory.
  • If dependencies conflict, retry in a fresh virtual environment, container, or working directory.
  • If output looks wrong, return to the smallest documented claude-seo example before adding complex data.
  • For keys, model files, or external services, verify environment variables, local paths, and permissions one by one.
  • Before production use, review recent updates, open issues, license terms, and safety boundaries.
What is claude-seo?

claude-seo is an open-source all project. Universal SEO skill for Claude Code. 25 sub-skills + 18 sub-agents covering technical SEO, E-E-A-T, schema, GEO/AEO, backlinks, local SEO, maps intelligence, semantic clustering, e-commerce SEO, international SEO, Google APIs, and PDF/Excel reporting. Optional DataForSEO, Firecrawl, and Banana extensions.

How do I install claude-seo?

Start with the official README. The first detected setup step is: git clone --depth 1 https://github.com/AgriciDaniel/claude-seo.git.

Is claude-seo beginner-friendly?

If you already know the Python ecosystem, start with the smallest example. Otherwise test it in an isolated environment first.

Can claude-seo be used commercially?

GitHub detected the MIT repository license, which generally permits commercial use. This signal only covers the repository license; review its obligations and any model weights, datasets, dependencies, or external services before commercial adoption.

Does claude-seo need a GPU?

GPU requirements depend on the workload, model, and dataset size. Start with the smallest README example before scaling up.

How should I decide whether to adopt claude-seo?

Evaluate setup cost, maintenance activity, issue health, license terms, and fit with your real workflow.

Star trend

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