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 Thibaultbm/claude-seo-geo --skill seo-internal-linkinggit clone --depth 1 https://github.com/Thibaultbm/claude-seo-geoWrote 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/thibaultbm/claude-seo-geo/seo-internal-linking)<a href="https://agentmods.dev/skills/thibaultbm/claude-seo-geo/seo-internal-linking"><img src="https://agentmods.dev/badge/skills/thibaultbm/claude-seo-geo/seo-internal-linking/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/thibaultbm/claude-seo-geo/seo-internal-linking"><img src="https://agentmods.dev/badge/skills/thibaultbm/claude-seo-geo/seo-internal-linking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00111 | $0.04370 |
| Opus 5 | $0.00056 | $0.02185 |
| Sonnet 5 | $0.00022 | $0.00874 |
| Haiku 4.5 | $0.00011 | $0.00437 |
Grade A, and why
seo-internal-linking 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 11d 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 — 274 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Internal Linking Architecture
Build the internal link graph that routes authority from blog content to commercial pages, leaves zero pages orphaned, and makes the site hierarchy legible to search engines and, through their indexes, to AI engines.
Company knowledge first (Obsidian)
If the working environment contains an Obsidian vault or any local knowledge base (a folder of .md notes, often with a .obsidian directory), read the relevant notes before acting: brand and product facts, target keywords, competitors, and the SEO action log of what was already tried. Ground every recommendation in that context instead of asking the user for facts the vault already holds. At the end of the session, append the actions taken to the vault's SEO action log so the next session starts informed. Vault structure, read-first and write-back protocols: the obsidian-brain skill.
When to use
- Planning internal links for a new article or page (which targets, which anchors, where).
- Auditing an existing site for orphan pages, weak structure, or money pages starved of links.
- Building topic clusters: mini-silos for niche sites, hub and spoke for large sites.
- Deciding what belongs in the menu and what belongs in the footer.
- Diagnosing a page that is indexed but gets no impressions or never ranks.
- Resolving keyword cannibalization between two pages (merge and 301 decisions).
- Migrating a blog from a subdomain to a subfolder.
Route adjacent jobs to their own skills:
- External link acquisition and link spots: seo-backlinks.
- Passage-level citability of a page in AI engines: geo-visibility.
- BreadcrumbList and other markup implementation: seo-schema-markup.
- Keyword-to-page mapping and intent analysis: seo-keyword-research.
- Writing the supporting articles themselves: seo-content-blog.
Workflow
Step 1. Map the money pages
List every page that sells: products, services, collections, pricing, signup, contact. Rank by business value:
- Direct revenue pages first: service pages, product pages, pricing.
- Assisted conversion pages second: comparison pages, case studies, contact.
- For each, record the current inbound internal links (count and source pages).
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.
- 11d ago First seen · 274 lines · 111 tokens per session scan A 85afebafc968
seo-internal-linking is a skill published in the GitHub repository Thibaultbm/claude-seo-geo (16 stars, last pushed today), licensed MIT. It adds 111 tokens to every session and 4,370 once invoked, about $0.0006 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 2026-08-30.
Other skills, from other repositories
geo-audit
Full website GEO+SEO audit with parallel subagent delegation. Orchestrates a comprehensive Generative Engine Optimization audit across AI citability, platform analysis, technical infrastructure, content quality, and schema markup. Produces a composite GEO Score (0-100) with prioritized action plan.
geo
GEO-first SEO analysis tool. Optimizes websites for AI-powered search engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) while maintaining traditional SEO foundations. Performs full GEO audits, citability scoring, AI crawler analysis, llms.txt generation, brand mention scanning, platform-specific…
geo-brand-mentions
Brand mention and authority scanner for AI visibility. Analyzes brand presence across platforms that AI models rely on for entity recognition and citation decisions. Produces a Brand Authority Score (0-100) with platform-specific recommendations.
geo-llmstxt
Analyzes and generates llms.txt files -- the emerging standard for helping AI systems understand website structure and content. Can validate existing llms.txt files or generate new ones from scratch by crawling the site.
agent-readiness-scan
Use when a client audit, GEO/AI-visibility snapshot, or remediation re-scan needs the Cloudflare agent-readiness score from isitagentready.com — e.g. Theo client audits, "is the site agent-ready", markdown negotiation / MCP / llms.txt / Content-Signal checks, or tracking score deltas after Tier 0/1 fixes.
found-by-ai
Measure whether AI engines actually recommend a business when buyers ask. Runs the free live scan at areyoufoundbyai.com (no auth, 60s), reads the verdict and the rivals AI names instead, hands back the fix plan, and wires monitored sites into a fix-and-re-measure loop over MCP.