keyword-clustering

keyword-clustering is a skill for Claude Code from akii-technologies-ltd/akii-seo-ai-search-optimizer. It costs 68 tokens per session (1,692 once invoked), scanned A, original, MIT.

A workflow that groups a raw list of search terms into related topic and intent groups for a website.

In plain words
What is it for?
It can identify pillar topics, supporting pages, search intent, search volume, difficulty, and the pages currently ranking for terms when those data sources are available. A pillar page is a broad main page supported by more focused related pages.
Why use it?
It turns an unorganized keyword list into a possible page structure and keeps searches with different goals apart.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the akii-seo-ai-search-optimizer plugin — 12 skills, 3 commands, 5 agents, 1 hook shipped together

Good fit It can identify pillar topics, supporting pages, search intent, search volume, difficulty, and the pages currently ranking for terms when those data sources are available. A pillar page is a broad main page supported by more focused related pages.

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Install with agentmods
npx agentmods add skills/akii-technologies-ltd/akii-seo-ai-search-optimizer/keyword-clustering
Install

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.

Any agent
npx skills add akii-technologies-ltd/akii-seo-ai-search-optimizer --skill keyword-clustering
Clone the repo
git clone --depth 1 https://github.com/akii-technologies-ltd/akii-seo-ai-search-optimizer

Made for: Claude Code.

Or install akii-seo-ai-search-optimizer, the plugin that ships this one along with the rest of its 12 skills, 3 commands, 5 agents, 1 hook.

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/akii-technologies-ltd/akii-seo-ai-search-optimizer/keyword-clustering/github.svg)](https://agentmods.dev/skills/akii-technologies-ltd/akii-seo-ai-search-optimizer/keyword-clustering)
Your own site
<a href="https://agentmods.dev/skills/akii-technologies-ltd/akii-seo-ai-search-optimizer/keyword-clustering"><img src="https://agentmods.dev/badge/skills/akii-technologies-ltd/akii-seo-ai-search-optimizer/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/akii-technologies-ltd/akii-seo-ai-search-optimizer/keyword-clustering"><img src="https://agentmods.dev/badge/skills/akii-technologies-ltd/akii-seo-ai-search-optimizer/keyword-clustering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 68 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,692 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 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 $0.00068 $0.01692
Opus 5 $0.00034 $0.00846
Sonnet 5 $0.00014 $0.00338
Haiku 4.5 $0.00007 $0.00169

Measured 13d ago against content hash d84a5234d306, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, 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 13d 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.

skills/keyword-clustering/SKILL.md · 82 lines

How it starts

The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Keyword Clustering

You are a keyword clustering specialist powered by Akii. Take a raw keyword list, output a coherent site architecture: pillar + cluster pages mapped to intent.

Data sources (auto-detect)

  • mcp__plugin_marketing_ahrefs__keywords-explorer-* — vol, KD, intent, parent topic
  • mcp__plugin_marketing_ahrefs__keywords-explorer-related-terms — to expand seed lists
  • WebSearch — to validate intent + SERP overlap when MCP unavailable

Steps

  1. Take keyword list (file path, pasted, or "expand from seeds" — name 5-15 seed topics and the skill expands via SERP-overlap or training-data inference).

  2. For each keyword, gather: search volume, difficulty, intent, top-ranking URL.

  3. Compute clustering:

    • With MCP: use Ahrefs "parent topic" or DataForSEO "common SERP results" for SERP-overlap clustering
    • Without MCP: lexical similarity + manual intent grouping with Claude as judge
  4. Intent split is a HARD constraint, not a soft suggestion. Never put informational and commercial keywords in the same cluster. If a seed topic has both ("AI visibility" = "what is AI visibility" + "AI visibility tool"), produce two separate clustersCluster N — AI visibility (informational) and Cluster N+1 — AI visibility (commercial). Do NOT produce a single mixed cluster with "Pillar A (info)" + "Pillar B (commercial)" — that's the same rule violation in a different shape.

  5. For each cluster, the default pillar is the highest-volume head term. The rest become cluster pages.

    Editorial override is allowed when the highest-volume term is too broad / competitive / off-brand for the site's specialization (e.g. a niche AI-search tool picking "Reddit citations in AI search — 540" over the generic "Reddit SEO — 1.4k" head term). When overriding the default, append [editorial override — highest-volume kw is "<term>" at <vol>] to the pillar row so the user sees both the chosen pillar AND what the volume-default would have been. Don't hide the override.

  6. Map each cluster to recommended URL structure: /pillar/<slug>/ + /pillar/<slug>/<cluster-slug>/.

  7. Tag each keyword row with provenance, same as the internal-linking skill:

    • [Ahrefs] — volume + KD pulled live from mcp__plugin_marketing_ahrefs__keywords-explorer-*
    • [heuristic] — estimated from training-data, no live source consulted
    • [alias] — keyword maps to the same URL as the cluster's pillar (no new page needed)
    • [absorbed] — head-term variant that the pillar page already targets directly When [Ahrefs] isn't available, EVERY volume + KD number ships with [heuristic] suffix. Never present heuristic estimates as Ahrefs-grounded data.

Read the full file on GitHub · 82 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. 13d ago First seen · 82 lines · 68 tokens per session scan A d84a5234d306

Subscribe to this mod's changes

keyword-clustering is a skill published in the GitHub repository akii-technologies-ltd/akii-seo-ai-search-optimizer (76 stars, last pushed 3mo ago), licensed MIT. It adds 68 tokens to every session and 1,692 once invoked, about $0.0003 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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