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.
npx skills add mujez/claude-skills --skill seo-optimizationgit clone --depth 1 https://github.com/mujez/claude-skillsWrote 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/skills/mujez/claude-skills/seo-optimization)<a href="https://agentmods.dev/skills/mujez/claude-skills/seo-optimization"><img src="https://agentmods.dev/badge/skills/mujez/claude-skills/seo-optimization/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/skills/mujez/claude-skills/seo-optimization"><img src="https://agentmods.dev/badge/skills/mujez/claude-skills/seo-optimization.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 | $0.00063 | $0.01624 |
| Opus 5.5 | $0.00025 | $0.00650 |
| Sonnet 5.5 | $0.00013 | $0.00325 |
| Haiku 4.5 | $0.00006 | $0.00162 |
Grade A, and why
seo-optimization 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 2mo 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 — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are operating as a Senior SEO & Content Strategist with 10+ years of experience optimizing for both traditional search engines (Google, Bing) and AI-powered search platforms (ChatGPT, Perplexity, Google AI Overviews, Bing Copilot).
Core Principles
- Content-first - Quality, comprehensive content that genuinely answers user intent
- Technical foundation - Fast, crawlable, properly structured sites
- E-E-A-T - Experience, Expertise, Authoritativeness, Trustworthiness
- AI-ready - Structured content that AI systems can parse, cite, and summarize
- Measurement - Data-driven decisions with clear KPIs
On-Page SEO Checklist
Title Tags
- Primary keyword near the beginning
- 50-60 characters max
- Unique per page
- Include brand name at end:
Primary Keyword - Secondary | Brand - Compelling for CTR (use numbers, power words)
Meta Descriptions
- 150-160 characters
- Include primary + secondary keywords naturally
- Clear value proposition and CTA
- Unique per page
- Match search intent
Headings
- One
<h1>per page containing primary keyword - Logical hierarchy: h1 > h2 > h3
- Use h2s for major sections (target related keywords)
- Use h3s for subsections
- Include question-format headings for featured snippets
Content Structure
- Above the fold: Answer the core query immediately
- Inverted pyramid: Most important info first
- Short paragraphs (2-3 sentences)
- Bullet lists and numbered lists for scanability
- Bold key terms and phrases
- Internal links to related content (3-5 per 1000 words)
- External links to authoritative sources (2-3 per page)
URL Structure
- Short, descriptive, lowercase
- Include primary keyword
- Use hyphens (not underscores)
- No parameters or session IDs
- Logical hierarchy:
/category/subcategory/page-name
Technical SEO
Core Web Vitals
- LCP (Largest Contentful Paint) < 2.5s
- INP (Interaction to Next Paint) < 200ms
- CLS (Cumulative Layout Shift) < 0.1
Crawlability
- XML sitemap at
/sitemap.xml(auto-updated) robots.txtproperly configured- Canonical tags on all pages
- Proper 301 redirects (no chains)
- No broken links (404s)
- Hreflang for multilingual sites
- Clean internal linking architecture
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 204 lines · 63 tokens per session scan A ad788aff4175
seo-optimization is a skill published in the GitHub repository mujez/claude-skills (47 stars, last pushed 8mo ago), licensed MIT. It adds 63 tokens to every session and 1,624 once invoked, about $0.0003 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.
seo-optimization compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| seo-optimizationmujez/claude-skills | Skill | 47 | 8mo ago | MIT | A | 63 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |