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-backlinksgit 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-backlinks)<a href="https://agentmods.dev/skills/thibaultbm/claude-seo-geo/seo-backlinks"><img src="https://agentmods.dev/badge/skills/thibaultbm/claude-seo-geo/seo-backlinks/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-backlinks"><img src="https://agentmods.dev/badge/skills/thibaultbm/claude-seo-geo/seo-backlinks.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 | $0.00111 | $0.07214 |
| Opus 5 | $0.00056 | $0.03607 |
| Sonnet 5 | $0.00022 | $0.01443 |
| Haiku 4.5 | $0.00011 | $0.00721 |
Grade A, and why
seo-backlinks 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 — 341 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO Backlinks: Strategy, Acquisition, and Brand Mentions
Most SEO tooling stops at link analysis: it tells you what your profile looks like and leaves you alone for the hard part. This skill covers the hard part: how to actually acquire links and brand mentions, by hand, with a defensible strategy, without a paid tool subscription and without an outreach agency.
It operates on a dual objective that defines off-page SEO in 2026:
- Links for Google. Backlinks remain a major ranking factor in classic organic search.
- Mentions everywhere for LLMs. Brand mentions (linked or not) correlate roughly 3x more strongly with visibility in AI answers than backlinks do. Ahrefs measured this across 75,000 brands: correlation of 0.664 for brand mentions versus 0.218 for backlinks against AI Overview presence (https://ahrefs.com/blog/ai-overview-brand-correlation/).
Every action this skill recommends should serve at least one of those two objectives, and the best actions serve both: a profile on a well-known platform is a link for Google and a citation surface for ChatGPT.
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 this skill
Use it when the user wants to:
- Review or audit a backlink profile (theirs or a competitor's).
- Build a link acquisition plan (weekly cadence, 90-day program, campaign).
- Execute ninja linking: find and work concrete link spots one by one.
- Decide whether a specific link opportunity is worth taking (or buying).
- Recover or understand a drop attributed to off-page factors (spam updates, lost links).
- Increase brand mentions so AI assistants cite the brand in answers.
What ships with it
2 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.
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 · 341 lines · 111 tokens per session scan A 388aaed02ff7
seo-backlinks 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 7,214 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.
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