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.
git clone --depth 1 https://github.com/XuanRanL/loamwright-SEO-SkillWrote 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/agents/xuanranl/loamwright-seo-skill/audit-cluster)<a href="https://agentmods.dev/agents/xuanranl/loamwright-seo-skill/audit-cluster"><img src="https://agentmods.dev/badge/agents/xuanranl/loamwright-seo-skill/audit-cluster/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/agents/xuanranl/loamwright-seo-skill/audit-cluster"><img src="https://agentmods.dev/badge/agents/xuanranl/loamwright-seo-skill/audit-cluster.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 | $0.00034 | $0.00982 |
| Opus 5 | $0.00017 | $0.00491 |
| Sonnet 5 | $0.00007 | $0.00196 |
| Haiku 4.5 | $0.00003 | $0.00098 |
Grade A, and why
audit-cluster 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Cluster Agent
Spawn Condition
Blog or pillar pages detected: crawl-results.json has page_type: "blog"|"pillar", OR site has 10+ content pages by URL pattern or word count.
Inputs
{audit_dir}/crawl-results.json— URLs, titles, H1, H2s, word count, internal links in/out{audit_dir}/config.json— domain, primary topics, competitor domains{audit_dir}/modules/content.json— content scores (if available)
Scripts
python -m scripts.audit.parse_html {html_path} --url {page_url} --json— the file is positional; output includes headings andlinks.internal/links.external(there are no--extract-*flags)
SERP-overlap cannibalization confirmation is NOT implemented — no serp_overlap
module exists under scripts/. Detect cannibalization by comparing H2 topics and
title keywords across pages from crawl-results.json (the "suspected" tier below);
never report the "confirmed" tier without real SERP data.
Checks
1. Pillar Identification
Criteria: 2000+ words, 5+ inbound internal links, broad topic scope, top-level URL. Output list with confidence.
2. Cluster Mapping
Per pillar, find cluster pages by: inbound links to pillar, URL prefix, titles matching pillar H2 subtopics, outbound links from pillar. Build {pillar_url: [cluster_urls]}.
3. Hub-Spoke Validation
Spoke→Hub: each cluster page links to its pillar (mandatory, target 100%). Hub→Spoke: pillar links to clusters (target 80%+). Spoke↔Spoke: sibling cross-links (beneficial). HIGH if < 50% spoke→hub; MEDIUM if 50-80%.
4. Cannibalization Detection
Compare pages pairwise (within clusters first, then cross). Signals: title token-overlap > 70%, identical H1 primary keyword, same keyword slug. With SERP data: both ranking = confirmed (CRITICAL). Without: suspected (HIGH). Pairs with different intent + proper linking = complementary (no issue).
5. Content Gaps
Build topic universe from: competitor sitemaps, pillar H2 subtopics not expanded, keyword lists. Cross-reference existing titles/H1s. Gaps = uncovered topics. Prioritize by volume potential and relevance to existing pillars.
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 · 64 lines · 34 tokens per session scan A 3db3b0adfa7d
audit-cluster is an agent published in the GitHub repository XuanRanL/loamwright-SEO-Skill (47 stars, last pushed 22d ago), licensed Apache-2.0. It adds 34 tokens to every session and 982 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 2026-08-30.
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