Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add ZachArticulateV/designer-pro-and-seo/plugin install designer-pro-and-seoWrote 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/zacharticulatev/designer-pro-and-seo/seo-cluster)<a href="https://agentmods.dev/skills/zacharticulatev/designer-pro-and-seo/seo-cluster"><img src="https://agentmods.dev/badge/skills/zacharticulatev/designer-pro-and-seo/seo-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/skills/zacharticulatev/designer-pro-and-seo/seo-cluster"><img src="https://agentmods.dev/badge/skills/zacharticulatev/designer-pro-and-seo/seo-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 | $0.00125 | $0.02191 |
| Opus 5 | $0.00063 | $0.01095 |
| Sonnet 5 | $0.00025 | $0.00438 |
| Haiku 4.5 | $0.00013 | $0.00219 |
Grade A, and why
seo-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 12d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
seo-cluster
Family: seo Status: Stable
Purpose
Plan content architecture as hub-and-spoke clusters: one pillar page per
cluster, supporting spoke articles linking to and from it, with an internal-link
matrix that specifies anchor text. Keywords are grouped by SERP overlap — if
Google returns the same pages for two keywords, they belong on one page; if it
returns different pages, they need separate pages. That shared-result signal, not
word or embedding similarity, is the only one that predicts whether a single URL can
rank for the group (see references/seo-cluster/serp-overlap-method.md). The pillar
is the most SERP-central keyword; the spokes specialize under it
(references/seo-cluster/hub-and-spoke.md).
Triggers
- "topic cluster" / "content cluster" / "semantic clustering"
- "pillar page" / "hub and spoke" / "content architecture"
- "keyword grouping" / "cluster plan"
Inputs
- Seed keywords (or a single seed to expand into a keyword set)
- Cluster-size / overlap threshold; region / language; SERP depth (top-N)
Steps
- Expand seeds into a keyword set (modifiers, questions, related terms).
- Acquire SERPs (this is the acquisition step, not the script). For each
keyword, gather the top-ranked URLs into a SERP blob — a JSON object
{keyword: [ranked urls]}. Free path: read SERPs with WebSearch. Tier-1 path: pull bulk live SERPs from a DataForSEO / Semrush MCP when connected. - Cluster deterministically over that blob:
python3 "${CLAUDE_PLUGIN_ROOT}/scripts/seo/serp_cluster.py" \ --serps serps.json --threshold 3 --top 10 --humanserp_cluster.pycomputes pairwise SERP overlap, clusters by shared-URL single-linkage at the chosen threshold, classifies each keyword's intent, picks the pillar, and emits the internal-link matrix. It never fetches anything and runs fully offline; it is the deterministic post-processor over the supplied blob. - Review roles — confirm the pillar (broad/head) and spokes (specific/long-tail) per cluster; split any visibly mixed-intent or over-merged cluster (the chaining caveat in the method reference).
- Render the cluster map: drop the script's JSON into
skills/seo-cluster/templates/cluster-map.html(replace the/*__SERP_CLUSTER_JSON__*/ nullsentinel — the marker plus thenullafter it — so both the template and the injected result stay valid JS) for an interactive hub-and-spoke view, plus the link matrix (CSV/markdown). Hand each pillar/spoke toseo-content-briefto brief the page.
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.
- 12d ago First seen · 137 lines · 125 tokens per session scan A 38d6f8ecca6e
seo-cluster is a skill published in the GitHub repository ZachArticulateV/designer-pro-and-seo (8 stars, last pushed 2mo ago), licensed MIT. It adds 125 tokens to every session and 2,191 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 2026-08-31.
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