open-seo: Skill for Claude Code

.agents/skills/keyword-clustering/SKILL.md

keyword-clustering is a skill for Claude Code, Codex from every-app/open-seo. It costs 17 tokens per session (1,033 once invoked), scanned A, original, MIT.

A keyword-mapping workflow that groups related search terms by what people intend to find and connects each group to an existing or proposed page. This grouping is called a keyword cluster.

In plain words
What is it for?
Use it to cluster keyword lists, map clusters to current URLs, identify missing pages, and decide which page should target each group.
Why use it?
It prevents several pages from competing for the same search terms and shows which topics need new pages. It ties keyword grouping to actual page planning.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is every-app/open-seo's own configuration. It tells Claude Code and Codex how to work on open-seo itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything open-seo configures →

About the project

OpenSEO is an open-source SEO platform for keyword research, rank tracking, competitor analysis, backlink analysis, site audits, and AI visibility work. It connects SEO data to AI agents through an MCP server and reusable agent skills, while allowing users to supply their own DataForSEO API key and self-host the tool. Catalogue add-ons guide agents through OpenSEO's SEO workflows.

every-app/open-seo · 18,020 stars · on GitHub · openseo.so

Reuse

Borrowing it

Nothing to install: this file belongs to every-app/open-seo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/every-app/open-seo/main/.agents/skills/keyword-clustering/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/every-app/open-seo

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for keyword-clustering

README.md
[![agentmods](https://agentmods.dev/badge/skills/every-app/open-seo/keyword-clustering/github.svg)](https://agentmods.dev/skills/every-app/open-seo/keyword-clustering)
Your own site
<a href="https://agentmods.dev/skills/every-app/open-seo/keyword-clustering"><img src="https://agentmods.dev/badge/skills/every-app/open-seo/keyword-clustering/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.

agentmods 80×15 button for keyword-clustering

Your own site · 80×15
<a href="https://agentmods.dev/skills/every-app/open-seo/keyword-clustering"><img src="https://agentmods.dev/badge/skills/every-app/open-seo/keyword-clustering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,033 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 20 Aug 2026
  • Snyk warn 20 Aug 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00017 $0.01033
Opus 5 $0.00009 $0.00517
Sonnet 5 $0.00003 $0.00207
Haiku 4.5 $0.00002 $0.00103

Measured 10d ago against content hash f4a53947527c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

keyword-clustering 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 10d 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.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

.agents/skills/keyword-clustering/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

OpenSEO Keyword Clustering

Goal

Group keywords into page-level clusters and decide which existing or new page should target each cluster. This is a keyword mapping workflow, not just a semantic grouping exercise.

Required inputs

  • projectId
  • A keyword list, saved keyword tag, seed topic, or target domain
  • Optional existing URLs/pages to map against

If keywords are not provided, use list_saved_keywords for saved sets, research_keywords for seed discovery, or get_ranked_keywords when the user starts from a target domain.

Project context

The project-context tools are free and shared with the app and other agents.

  1. Call get_project_context first and ground the mapping in it — the saved key pages are the existing pages clusters should map to, and the business and goal decide which clusters are worth targeting.
  2. This skill needs key pages. If none are saved, run a minimal inline setup: ask the user for the pages that matter, or propose a shortlist from the site, an audit, or Search Console and confirm it, write it back with update_project_context (addKeyPages), then continue the clustering. Never front-load the full interview; suggest seo-project-setup at the end for the rest.
  3. Before spending credits, check the research log. If the same research ran within the last 30 days, reuse that result and say so instead of re-buying it.
  4. On finish, write back what is durable with update_project_context — new or corrected addKeyPages entries with the topic each page now targets — and append a research log entry: { appendResearchLog: { summary: "Keyword clustering: <keyword set>. Verdict: <conclusion>" } }.

OpenSEO MCP tools

  • list_saved_keywords: fetch an existing keyword set, optionally filtered by tags.
  • research_keywords: expand a seed when the user starts from a topic.
  • get_ranked_keywords: gather exact ranking keywords and URLs when the user starts from a domain or page.
  • get_search_console_performance: when Search Console is connected, pull real queries with dimensions: ["query","page"] to map terms to the pages already earning impressions and to surface cannibalization (one query splitting clicks across multiple URLs).
  • get_serp_results: validate whether keywords belong on the same page by checking SERP overlap and intent.
  • get_local_serp_results: use for local SEO clusters when Maps/local-pack intent should affect page mapping.
  • save_keywords: optionally tag final clusters after user confirmation.

Read the full file on GitHub · 86 lines

Changes

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.

  1. 10d ago First seen · 86 lines · 17 tokens per session scan A f4a53947527c

Subscribe to this mod's changes

keyword-clustering is a skill published in the GitHub repository every-app/open-seo (18,020 stars, last pushed 6d ago), licensed MIT. It adds 17 tokens to every session and 1,033 once invoked, about $0.0001 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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