agentmods.dev

upgradeseo: Skill for Claude Code

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

keyword-clustering is a skill for Claude Code, Codex from upgrade-ventures/upgradeseo. It costs 17 tokens per session (784 once invoked), scanned A, a copy of keyword-clustering, MIT.

An SEO workflow for grouping related search terms by what the searcher wants and assigning each group to an existing or proposed page. This is called keyword mapping.

In plain words
What is it for?
Clustering supplied or discovered keywords, checking overlap in search results, mapping terms to URLs, and finding possible keyword cannibalization.
Why use it?
It reduces the risk of creating unnecessary pages or having several pages compete for the same search term. It also connects search research to a concrete content plan.

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 upgrade-ventures/upgradeseo's own configuration. It tells Claude Code and Codex how to work on upgradeseo 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 upgradeseo configures →

not rated 1repo +1 22d ago A scan 17 tokens copy · 84% MIT
View source ↗ upgrade-ventures/upgradeseo upgrade.ventures
Reuse

Borrowing it

Nothing to install: this file belongs to upgrade-ventures/upgradeseo. 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/upgrade-ventures/upgradeseo/main/.agents/skills/keyword-clustering/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/upgrade-ventures/upgradeseo

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/upgrade-ventures/upgradeseo/keyword-clustering/github.svg)](https://agentmods.dev/skills/upgrade-ventures/upgradeseo/keyword-clustering)
Your own site
<a href="https://agentmods.dev/skills/upgrade-ventures/upgradeseo/keyword-clustering"><img src="https://agentmods.dev/badge/skills/upgrade-ventures/upgradeseo/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/upgrade-ventures/upgradeseo/keyword-clustering"><img src="https://agentmods.dev/badge/skills/upgrade-ventures/upgradeseo/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 784 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.
Origin 84% copy Near-identical to another mod 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 $0.00784
Opus 5 $0.00009 $0.00392
Sonnet 5 $0.00003 $0.00157
Haiku 4.5 $0.00002 $0.00078

Measured 9d ago against content hash dba8e596edb3, 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 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.

Origin

This is a copy

84% identical to keyword-clustering — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/keyword-clustering/SKILL.md · 77 lines

How it starts

The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.

UpgradeSEO 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.

UpgradeSEO 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.

Workflow

  1. Gather the candidate keyword set.
    • Use get_search_console_performance (dimensions ["query","page"]) when Search Console is connected to start from real queries and the pages already ranking for them.
    • Use get_ranked_keywords for domain/page-driven clustering.
    • Use search_local_businesses and get_local_serp_results when proximity, local packs, or Google Business results determine whether terms belong on location pages.
  2. Remove duplicates, irrelevant terms, and terms that clearly require a different product or audience.
  3. Build clusters around intent and page type:
    • Same SERP intent and similar ranking pages belong together.
    • Different intent, buyer stage, or SERP format should be split.
    • Similar words do not guarantee the same cluster.
  4. For important borderline terms, use a small get_serp_results batch to check overlap.
  5. Assign each cluster to:
    • Existing URL, if supplied and appropriate
    • New page recommendation, if no existing page fits
    • Do-not-target / later bucket, if weak or off-strategy
  6. Identify cannibalization risk when multiple pages would target the same intent. When Search Console is connected, confirm it from real data with get_search_console_performance (dimensions: ["query","page"]) — the same query sending impressions to multiple URLs.
  7. Ask before applying cluster tags with save_keywords.

Read the full file on GitHub · 77 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. 9d ago First seen · 77 lines · 17 tokens per session scan A dba8e596edb3

Subscribe to this mod's changes

keyword-clustering is a skill published in the GitHub repository upgrade-ventures/upgradeseo (1 stars, last pushed 22d ago), licensed MIT. It adds 17 tokens to every session and 784 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 84% identical to keyword-clustering, differing in 13 lines, and is treated as a copy.

Marketing and SEOahrefs-alternativebacklinkscloudflare-workerskeyword-researchmcpopen-source
Related

Other skills, from other repositories

semrush-backlink-audit

Audit backlink profiles with the semrush CLI. Use when the user asks for backlink analysis, referring domains, authority score, anchor text, indexed linked pages, backlink competitors, link gaps, backlink history, toxic or suspicious link signals, or off-page SEO recommendations based on Semrush CLI backlink data.

osodevops/intelligence-layer-skills · 66 tokens

semrush-batch-workflows

Create, estimate, run, and adapt semrush CLI TOML batch recipes. Use when the user needs reusable Semrush CLI workflows, competitor audit recipes, keyword opportunity recipes, backlink audit recipes, paid-search recipes, traffic summary recipes, scheduled SEO data pulls, or API-unit estimates before multi-step Semrush…

osodevops/intelligence-layer-skills · 70 tokens

semrush-cli-setup

Install, configure, validate, and troubleshoot the semrush CLI. Use when the user needs Semrush API auth, SEMRUSHAPIKEY or SEMRUSHOAUTHTOKEN setup, output/cache/rate-limit configuration, shell completions, API balance checks, structured error handling, or a prerequisite check before running other Semrush CLI skills.

osodevops/intelligence-layer-skills · 74 tokens

semrush-competitor-research

Analyze SEO competitors, organic keywords, top pages, subdomains, and keyword gaps with the semrush CLI. Use when the user asks for competitor research, organic competitor discovery, content gaps, domain comparison, missing or untapped keywords, page-level SEO opportunities, or a competitive SEO audit using Semrush…

osodevops/intelligence-layer-skills · 71 tokens

semrush-keyword-research

Research, expand, score, and prioritize SEO keywords with the semrush CLI. Use when the user asks for keyword research, search volume, CPC, difficulty, related keywords, broad-match keywords, question keywords, keyword clustering inputs, SERP domains for a query, or a prioritized keyword opportunity table powered by…

osodevops/intelligence-layer-skills · 73 tokens

semrush-local-seo

Manage and analyze local SEO data with semrush CLI v4 commands. Use when the user asks for Semrush local listings, local business location records, Google Maps or map-rank campaigns, map-rank keywords, heatmaps, local competitors, NAP/listing QA, or local SEO reporting through the Semrush CLI.

osodevops/intelligence-layer-skills · 71 tokens