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 JakeLabate/Claude-SEO-Skills --skill external-link-auditgit clone --depth 1 https://github.com/JakeLabate/Claude-SEO-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/jakelabate/claude-seo-skills/external-link-audit)<a href="https://agentmods.dev/skills/jakelabate/claude-seo-skills/external-link-audit"><img src="https://agentmods.dev/badge/skills/jakelabate/claude-seo-skills/external-link-audit/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/jakelabate/claude-seo-skills/external-link-audit"><img src="https://agentmods.dev/badge/skills/jakelabate/claude-seo-skills/external-link-audit.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 | $0.00090 | $0.01519 |
| Opus 5.5 | $0.00036 | $0.00608 |
| Sonnet 5.5 | $0.00018 | $0.00304 |
| Haiku 4.5 | $0.00009 | $0.00152 |
Grade A, and why
external-link-audit 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 1mo 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
External Link Audit
Audit the external (outbound) links of a website and produce an actionable SEO report.
When to use this skill
Use this skill when the user asks to:
- Audit or analyze external/outbound links on a website
- Find broken external links (link rot) or redirected destinations
- Check affiliate, sponsored, or paid links for correct
relattribution - Find insecure
http://outbound links or unsafetarget="_blank"usage - Review which external domains a site links to and how often
Inputs to collect
Before starting, confirm with the user:
- Site URL or local files — a live site root URL (e.g.,
https://example.com), a sitemap URL, or a local folder of HTML files. - Scope — full site, a specific section (e.g.,
/blog/), or a list of URLs. - Crawl limits — max pages (default 500) and max depth (default 5) for live crawls.
- Known paid/affiliate domains — domains that must carry
rel="sponsored"(e.g.,amzn.to, affiliate networks), if any.
Workflow
Step 1: Gather the page set and extract external links
- If a sitemap is available (
/sitemap.xml), fetch it to get the canonical page list. - Otherwise, crawl from the homepage following only same-host links.
- For local HTML folders, enumerate all
.htmlfiles.
Use scripts/extract_external_links.py to crawl the site and collect every external link into a JSON inventory:
python3 scripts/extract_external_links.py https://example.com --max-pages 500 --max-depth 5 --output external_links.json
# already crawled once (e.g. in a full SEO audit)? skip the crawl and reuse the shared cache:
# python3 scripts/fetch_pages.py https://example.com --output page_cache.json
# python3 scripts/extract_external_links.py --from-cache page_cache.json --output external_links.json
For every external link, the inventory records: source page, target URL, target domain, anchor text, rel attributes, target attribute, and whether the link is in <nav>/<footer> or in main content.
What ships with it
7 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.
- 1mo ago First seen · 122 lines · 90 tokens per session scan A 1ce7f8550035
external-link-audit is a skill published in the GitHub repository JakeLabate/Claude-SEO-Skills (3 stars, last pushed 4mo ago), licensed MIT. It adds 90 tokens to every session and 1,519 once invoked, about $0.0004 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 2026-08-31.
Other skills, from other repositories
seo-audit
A checklist-based SEO review for a website. SEO, or search engine optimization, is the work of improving a site so search engines can understand and rank it.
geo-content-research
Researches what prompts people ask AI engines (ChatGPT, Gemini, Perplexity, Claude) about a product category and produces a prompts.csv artifact — a prioritized, strictly-schema'd list of the queries where the brand should be cited. Feeds the monitor workflow.
create-geo-charts
Creates data visualizations (charts, graphs, tables) optimized for AI engine parsing and citation. Produces inline SVG/HTML with text summaries, data tables, and JSON-LD so AI engines can quote the data.
research-keywords
Finds high-value SEO and GEO keywords using web search, AI analysis, and optionally paid tools like Ahrefs or Semrush. Produces a validated keywords.csv file with a fixed schema for downstream pipeline consumption.
audit-content
Verifies truthfulness, accuracy, and link integrity of content before publishing. Catches fabricated statistics, dead URLs, misattributed sources, and company claims that contradict the brand DNA.
geo-content-planning
Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.