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 The-AI-Directory-Company/agents-and-skills --skill on-page-sgeogit clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-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/the-ai-directory-company/agents-and-skills/on-page-sgeo)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/on-page-sgeo"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/on-page-sgeo/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/the-ai-directory-company/agents-and-skills/on-page-sgeo"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/on-page-sgeo.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 | $0.00048 | $0.05671 |
| Opus 5 | $0.00024 | $0.02835 |
| Sonnet 5 | $0.00010 | $0.01134 |
| Haiku 4.5 | $0.00005 | $0.00567 |
Grade A, and why
on-page-sgeo 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 8d 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 — 442 lines — stays where its author put it; the contents beside it link to each section on GitHub.
On-Page SGEO Optimization
On-page SGEO (Search Generative Engine Optimization) is the practice of optimizing individual page elements so the page both ranks in traditional search results and gets cited by AI platforms (ChatGPT, Perplexity, Gemini, Copilot). Every section below addresses both dimensions together — SEO impact and GEO impact are not separate concerns.
This is skill 2 of 4 in the SGEO series: technical-sgeo > on-page-sgeo > content-sgeo > off-page-sgeo.
Before you start
Gather the following from the user. If anything is missing, ask before proceeding:
- Target page URL — The live URL being optimized, or a description of the page being created.
- Primary keyword / topic — The main query or subject the page should rank for and be cited on.
- Search intent — Informational, navigational, commercial, or transactional. This determines the optimal page structure.
- Target audience — Who this page is for (developers, marketers, executives, general consumers, etc.).
- Existing performance data — Google Search Console impressions, average position, CTR, and top queries if the page already exists. Omit for new pages.
- AI citation priority — Whether this page should be optimized for AI citation (high, medium, low). High priority pages get extra GEO formatting.
- Related pages on the site — Pages that should link to/from this one. Needed for internal linking recommendations.
- Competitor pages ranking for the same keyword — Top 3-5 URLs currently ranking, for gap analysis.
Tool discovery
Before gathering project details, confirm which tools are available. Ask the user directly — do not assume access to any external service.
Free tools (no API key required):
- WebFetch (fetch any public URL — robots.txt, sitemaps, pages)
- WebSearch (search engine queries for competitive analysis)
- Google PageSpeed Insights API (CWV data, no key needed for basic usage)
- Google Rich Results Test (structured data validation)
- Playwright MCP or Chrome DevTools MCP (browser automation)
What ships with it
13 files 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.
- references/geo-formatting.md 10 KB
- references/heading-and-structure.md 5.8 KB
- references/image-and-media.md 5.7 KB
- references/internal-linking.md 6.3 KB
- references/meta-optimization.md 5.6 KB
- scripts/analyze-headings.py 5.9 KB runs code
- scripts/audit-page.py 15 KB runs code
- scripts/check-direct-answer.py 9.1 KB runs code
- scripts/check-freshness.py 12 KB runs code
- scripts/check-images.py 7.3 KB runs code
- scripts/check-internal-links.py 7.6 KB runs code
- scripts/extract-meta-tags.py 7.1 KB runs code
- scripts/extract-structured-data.py 8.1 KB runs code
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.
- 8d ago First seen · 442 lines · 48 tokens per session scan A 2979b33fe697
on-page-sgeo is a skill published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 48 tokens to every session and 5,671 once invoked, about $0.0002 per session on Opus 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 2026-09-03.
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