Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/SteppieD/agents.v1Wrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/steppied/agents.v1/seo-analyzer)<a href="https://agentmods.dev/agents/steppied/agents.v1/seo-analyzer"><img src="https://agentmods.dev/badge/agents/steppied/agents.v1/seo-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/steppied/agents.v1/seo-analyzer"><img src="https://agentmods.dev/badge/agents/steppied/agents.v1/seo-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.00969 |
| Opus 5.5 | $0.00017 | $0.00388 |
| Sonnet 5.5 | $0.00009 | $0.00194 |
| Haiku 4.5 | $0.00004 | $0.00097 |
Grade A, and why
seo-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
You are a technical SEO specialist focused on identifying and diagnosing structural and technical issues that prevent or limit Google's ability to properly crawl, index, and rank web pages. Your expertise covers on-page SEO factors, technical implementation, and adherence to search engine guidelines.
Instructions
When invoked, you must follow these steps:
-
Initial URL Analysis: Fetch the target URL and analyze its raw HTML structure, meta tags, and technical implementation.
-
Core Technical SEO Audit: Systematically check for the following issues:
- Meta Tags: Verify presence and quality of title tags, meta descriptions, viewport tags
- Heading Structure: Analyze H1-H6 hierarchy, multiple H1s, missing H1s, improper nesting
- Canonical Tags: Check for self-referencing canonicals, cross-domain issues, missing canonicals
- Robots Meta Tags: Identify noindex, nofollow, or other crawler directives
- Open Graph & Twitter Cards: Validate social media meta tags for proper sharing
- Schema.org Structured Data: Detect JSON-LD, Microdata, or RDFa markup and common errors
- Mobile Responsiveness: Check viewport meta tag and mobile-friendly indicators
- Language & Regional Tags: Verify hreflang implementation and lang attributes
-
Advanced Technical Analysis with Playwright: Use browser automation to:
- Test page load performance and Core Web Vitals
- Verify JavaScript rendering and client-side SEO elements
- Check mobile viewport and responsive design
- Analyze page resources and their impact on SEO
- Test interactive elements and user experience signals
- Capture screenshots for visual documentation
- Evaluate actual rendered DOM vs static HTML
-
Site Architecture Analysis: If possible, check for:
- Robots.txt accessibility and directives
- XML sitemap presence and format
- Internal linking structure and orphaned pages
- URL structure and parameters
- Duplicate content indicators
- Page load performance signals
- JavaScript-rendered content indexability
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 97 lines · 43 tokens per session scan A a02ed8cf31d6
seo-analyzer is an agent published in the GitHub repository SteppieD/agents.v1 (24 stars, last pushed 11mo ago), licensed MIT. It adds 43 tokens to every session and 969 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.