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 content-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/content-sgeo)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/content-sgeo"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/content-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/content-sgeo"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/content-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 | $0.00052 | $0.04965 |
| Opus 5 | $0.00026 | $0.02482 |
| Sonnet 5 | $0.00010 | $0.00993 |
| Haiku 4.5 | $0.00005 | $0.00496 |
Grade A, and why
content-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 9d 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 — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content SGEO Strategy
Before you start
Gather the following from the user before planning or creating any content:
- What should content achieve? (Lead generation, signups, brand awareness, topical authority, investor credibility — pick a primary goal)
- Who is the target audience? (Job titles, experience levels, industries. "Everyone" is not an audience.)
- What content already exists? (Number of published pages, topics covered, current traffic levels. An audit URL or sitemap helps.)
- Who are the competitors? (3-5 sites that rank for the same topics. Needed for gap analysis in Step 1.)
- Is Google Search Console connected? (Existing query data accelerates keyword research and reveals quick wins at positions 4-15.)
- What resources are available? (Who writes? How many pieces per month? Budget for tools like Ahrefs, Semrush, or Clearscope?)
- How important is AI citation? (Some businesses prioritize appearing in ChatGPT, Perplexity, or Gemini answers. Others only care about Google rankings. This changes content structure.)
- What is the timeline? (SEO compounds over 3-6 months. GEO citation can be faster but fluctuates. Set expectations early.)
If the user says "we need more content," push back: "More content without keyword research, intent mapping, and a cluster strategy creates noise. What specific business outcome should content drive in the next quarter?"
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)
Paid tools (API key or MCP required):
- Google Search Console API (requires OAuth)
- DataForSEO MCP (SERP data, keyword metrics, backlinks)
- Ahrefs API (backlink profiles, keyword research)
- Semrush API (competitive analysis, keyword data)
What ships with it
12 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/content-refresh.md 8.1 KB
- references/eeat-signals.md 11 KB
- references/geo-content-framework.md 19 KB
- references/keyword-research.md 12 KB
- references/topic-clusters.md 9.5 KB
- scripts/analyze-serp-competitors.py 12 KB runs code
- scripts/audit-content-freshness.py 14 KB runs code
- scripts/check-eeat-signals.py 14 KB runs code
- scripts/classify-intent.py 11 KB runs code
- scripts/plan-topic-cluster.py 17 KB runs code
- scripts/research-keywords.py 13 KB runs code
- scripts/score-content-geo.py 25 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.
- 9d ago First seen · 285 lines · 52 tokens per session scan A fe2bb4b1970a
content-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 52 tokens to every session and 4,965 once invoked, about $0.0003 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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