seo-keyword-mapper

Compiles seed terms and keyword-tool exports into a structured SEO keyword map.

21|3|Updated Mar 6, 2026
One-click install
npx skills add https://github.com/peter-tu-zynkr/zynkr-skill-builder --skill seo-keyword-mapper-peter-tu-zynkr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: seo-keyword-mapper
Source: https://github.com/peter-tu-zynkr/zynkr-skill-builder/tree/main/skills/1-brand-marketing/seo-keyword-mapper
Command: npx skills add https://github.com/peter-tu-zynkr/zynkr-skill-builder --skill seo-keyword-mapper-peter-tu-zynkr

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Turning raw keyword-tool exports and seed terms into an organized keyword map is manual and error-prone, and teams often fabricate or lose search volume data in the process. This Skill structures that step of the SEO pipeline so every keyword is traced to its angle, volume, and difficulty. ## Core Features & Use Cases - Seed Term Expansion: Reads seed terms from an SEO_PACKET Angles handoff and expands them using a keyword checklist covering long-tail, question-style, and BOFU decision keywords. - Tool-Grounded Data: Organizes Ubersuggest and AnswerThePublic exports pasted by the user, marking missing volume or difficulty as pending instead of inventing numbers. - Structured Handoff: Produces a SEO_PACKET KeywordMap block and saves a working file to Google Drive for the next pipeline stage. - Use Case: After receiving an angles packet for a zh-TW article, ask the Skill to build the keyword map, paste your Ubersuggest export, and receive a thread-head-to-keyword map ready for intent classification. ## Quick Start Hand over your SEO_PACKET Angles and a pasted Ubersuggest or AnswerThePublic export and ask the assistant to build the complete keyword map.

Frequently Asked Questions about seo-keyword-mapper

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an SEO keyword map from Ubersuggest data?▼

Feed your seed terms into Ubersuggest, paste the export with search volume and difficulty into the Skill, and it organizes terms into a thread-head-to-keyword map following the keyword checklist. Missing data is marked as pending rather than fabricated.

What keyword tools work with this SEO workflow?▼

The workflow uses Ubersuggest for keyword ideas, volume, and SEO difficulty, and AnswerThePublic for questions, prepositions, and comparison terms. The user runs these tools manually and pastes the exports back for compilation.

Does the keyword mapper classify keywords by search intent?▼

No, intent classification is explicitly out of scope and handled by the downstream seo-keyword-classifier skill. This Skill only builds the map with volume, difficulty, angle origin, and language annotations.

What happens if keyword volume data is unavailable?▼

Entries without tool data are marked as volume or difficulty pending, or TBD in the checklist. The Skill never invents search volume or difficulty numbers, keeping the map grounded in real tool exports.

Can I use this for Traditional Chinese SEO keywords?▼

Yes, zh-TW is the primary language for keyword entries, with English recorded separately for flagship topics. The coverage check flags topics that need an EN version.