technical-seo

31 stars 7 forks

Use when diagnosing crawl/index issues, performance regressions, or structured data gaps.

Marketplace

Also in: data analysis

Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

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Claude Code (CLI) Fast

skilz install gtmagents/gtm-agents/technical-seo

OpenCode (CLI) Fast

skilz install gtmagents/gtm-agents/technical-seo --agent opencode

OpenAI Codex (CLI) Native

skilz install gtmagents/gtm-agents/technical-seo --agent codex

Gemini CLI (Project) Project

skilz install gtmagents/gtm-agents/technical-seo --agent gemini

First time? Install Skilz: pip install skilz

Works with 14 AI coding assistants

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

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For Claude Desktop Easy

Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

Manual Installation

1. Clone the repository:

git clone https://github.com/gtmagents/gtm-agents

2. Copy the agent skill directory:

cp -r gtm-agents/plugins/seo/skills/technical-seo ~/.claude/skills/

Owner: gtmagents (GitHub)
Repository: gtm-agents
Stars: 31
Forks: 7
Type: Technical
Meta-Domain: data ai
Primary Domain: database
Market Score: 60

Agentic Skill Grades →

Agent Skill Grade

Score: 60/100 Click to see breakdown

Score Breakdown

Spec Compliance

12/15

PDA Architecture

12/30

Ease of Use

17/25

Writing Style

8/10

Utility

10/20

Modifiers: +1

Recommendations

Focus on improving Pda (currently 12/30)
Focus on improving Utility (currently 10/20)
Add trigger phrases to description for discoverability

Graded: 2026-01-19

Developer Feedback

I took a look at your technical-seo skill and wanted to share some thoughts.

Links:

The TL;DR

You're at 60/100, D grade territory — this is based on Anthropic's skill best practices. The good news: your spec compliance is solid (12/15). The tough news: Progressive Disclosure Architecture and Utility are dragging you down hard (12/30 and 10/20 respectively). You've got the foundation right, but the skill needs more depth and structure to really shine.

What's Working Well

Spec compliance is tight — Your frontmatter is valid YAML with all required fields, name convention is correct hyphen-case. That's the baseline done right.
Readable structure — The skill has decent navigation signals with clear headers and what looks like a logical TOC, which helps discoverability.
Concise writing — Your content isn't bloated. You're saying what needs to be said without fluff (that's worth points in the Writing Style category).

The Big One: Reference Files Are Missing

Here's what's holding you back: you have zero reference files supporting your main SKILL.md. The grading report shows "0 reference files with 0 words" — that's a killer for Progressive Disclosure Architecture (which you need for the full 30 points).

Why this matters: A skill with only one 387-word SKILL.md file can't progressively disclose its complexity. Users get dumped the whole thing at once instead of layered discovery. This is a token efficiency problem AND a usability problem.

The fix: Create reference files. Think:

guides/getting-started.md — onboarding steps
examples/common-audits.md — real-world use cases
reference/tools-explained.md — detailed tool explanations
templates/audit-checklist.md — templates users can ...

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