Conqueror Keyword Clustering turns keyword and Search Console data into intent-based page plans with URL mappings and cannibalization alerts.
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1. ClawHub CLI
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npx clawhub@latest install conqueror-keyword-clustering
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
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Help me install conqueror-keyword-clustering using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
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What is Conqueror Keyword Clustering?
Conqueror Keyword Clustering is an SEO planning workflow that groups keywords by search intent, SERP overlap, buyer stage, and page type rather than relying on lexical similarity alone. It connects to a Conqueror MCP server to gather saved keywords, discover seed topics, retrieve ranked keywords, inspect Search Console queries, and validate local or standard SERPs.
The skill maps each cluster to an existing URL, a proposed new page, or a do-not-target bucket. It also produces page briefs, prioritization notes, internal-link opportunities, and cannibalization warnings when multiple URLs compete for the same query. As part of Openclaw Skills, it is designed to make keyword research more actionable and convert SEO data into a practical content plan.
Conqueror Keyword Clustering Use Cases
- Create a page-level content plan from a keyword list, saved keyword tag, seed topic, or target domain.
- Use Google Search Console queries and pages to identify real ranking relationships and cannibalization.
- Map keywords to existing URLs that already match the search intent.
- Recommend new landing pages when no current URL adequately serves a cluster.
- Separate keywords with different intent, buyer stages, audiences, products, or SERP formats.
- Validate borderline clusters through standard SERP overlap analysis.
- Build local SEO clusters where proximity, Maps, local-pack results, or Google Business intent affects page mapping.
- Flag weak, irrelevant, or off-strategy keywords for a do-not-target or later bucket.
- Prepare confirmed clusters for optional keyword tagging in Conqueror.
How Conqueror Keyword Clustering Works
- Confirm the required
projectIdand collect a keyword list, saved keyword set, seed topic, target domain, or optional existing URLs. - Gather candidate terms using
get_search_console_performancewith query and page dimensions,get_ranked_keywords,list_saved_keywords, orresearch_keywords, depending on the starting data. - For local SEO projects, use local business and local SERP data when proximity or local-pack intent influences page selection.
- Remove duplicates, irrelevant terms, and queries that clearly target a different product, audience, or business objective.
- Group terms by search intent and page type. Keywords with different intent, buyer stages, or SERP formats are split even when their wording is similar.
- Test important borderline terms with a focused
get_serp_resultsbatch to compare ranking-page overlap and validate whether they belong together. - Map every cluster to an appropriate existing URL, a proposed new page, or a do-not-target/later bucket.
- Review potential cannibalization, especially where multiple pages appear for the same query or would target the same intent.
- Produce a mapping summary, cluster table, and page brief covering page type, searcher problem, required sections, internal links, and tagging recommendations.
- Ask for explicit confirmation before applying cluster tags with
save_keywords.
Conqueror Keyword Clustering Setup
- Connect a Conqueror MCP server to the Openclaw-compatible agent environment. The source skill requires this connection and does not define a separate package installation command.
- Provide the required Conqueror
projectId. - Prepare at least one input source: a keyword list, saved keyword tag, seed topic, target domain, or optional list of existing URLs.
- Ensure Search Console is connected if the workflow should use real query-to-page performance and confirm cannibalization from impressions across multiple URLs.
- Request the clustering workflow and specify whether the focus is standard SEO, local SEO, existing-page mapping, new-page planning, or consolidation.
- Review the generated mapping before approving any changes. Cluster tagging through
save_keywordsis optional and requires explicit user confirmation.
No standalone CLI installation is specified by the skill; configuration is performed through the connected Conqueror MCP server and its available tools.
Conqueror Keyword Clustering Data Schema & Taxonomy
Required inputs
| Field | Purpose |
|---|---|
projectId |
Identifies the Conqueror project used for research and keyword operations. |
| Keyword source | A keyword list, saved keyword tag, seed topic, or target domain. |
| Existing URLs/pages | Optional references used to map clusters to current content. |
Research and validation data
list_saved_keywords: Retrieves existing keyword sets, optionally filtered by tags.research_keywords: Expands a seed topic into candidate terms.get_ranked_keywords: Retrieves ranking keywords and URLs for a domain or page.get_search_console_performance: Uses query and page dimensions to connect real queries with ranking URLs and detect split performance.get_serp_results: Checks standard SERP overlap and intent.get_local_serp_results: Validates local-pack and location-based intent.search_local_businesses: Supplies local business context when location affects page mapping.
Cluster record
| Field | Description |
|---|---|
| Cluster | The grouped keyword topic or intent set. |
| Primary keyword | The main term representing the target page. |
| Secondary keywords | Supporting terms assigned to the same page. |
| Intent | The dominant search purpose and buyer stage. |
| Target page | Existing URL, proposed new page, or do-not-target/later status. |
| Priority | Recommended implementation importance. |
| Notes | SERP evidence, cannibalization risks, or mapping rationale. |
Page brief metadata
Each cluster brief contains page type, the searcher problem, required sections, internal-link opportunities, and a save/tag suggestion. The output also summarizes total clusters, pages to create, existing pages to update, and consolidation or cannibalization issues.
Conqueror Keyword Clustering Advanced Features
- Search Console-aware clustering uses
dimensions: ["query", "page"]to identify queries whose impressions or clicks are split across multiple URLs. - SERP-first validation prevents clusters from being created solely from word similarity.
- Local SEO support accounts for proximity, Maps results, local packs, and Google Business intent.
- Flexible input discovery supports saved keyword sets, seed expansion, ranked-domain research, and performance data.
- Existing-page mapping distinguishes content updates from genuinely new page opportunities.
- Do-not-target and later buckets protect the plan from weak, irrelevant, or off-strategy terms.
- Cannibalization detection highlights consolidation opportunities before new content is published.
- Confirmation-gated
save_keywordstagging helps prevent broad or unintended taxonomy changes. - Small keyword sets are handled proportionally: fewer than 10 usable terms produce a simple map instead of forced over-clustering.
- The structured output combines an executive mapping summary, cluster table, and actionable page briefs for content and SEO teams.
- This workflow extends the practical value of Openclaw Skills by connecting research, technical validation, content architecture, and implementation decisions.
SKILL.md
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