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category-narrative-mapper ✓ Security reviewed
Use when the user asks to "map the category narrative", "tear down how competitors tell their sto…
⚡ Productivity By aaron-he-zhu Version v1.0.0 Updated 2026-09-03
6.7Overall rating

Installation

🤖 Install via AI

Copy the prompt below and send it to your AI assistant (e.g. Claude Code) — it will follow the instructions and install automatically.

Install the "category-narrative-mapper" skill by following the instructions at https://skill123.me/install/category-narrative-mapper.
⌨️ Command line install

Run in your terminal — downloads and installs to ~/.claude/skills/.

curl -fsSL https://skill123.me/install/category-narrative-mapper.sh | bash
📦 Download ZIP

Download the zip and extract it into your skills directory (e.g. ~/.claude/skills/), then restart your session.

⬇ Download v1.0.0 · 5 KB

About this skill

Overview

Use when the user asks to "map the category narrative", "tear down how competitors tell their story", or "find the language conventions in our market"; produces a category narrative map — the dominant stories and points of view in the category, its language conventions and framing clichés, and a per-competitor narrative teardown (arc, claimed onlyness, proof pattern) plus how each rival''s messaging has shifted over time (scraped copy vs archived copy). Not for the positioning canvas itself — use positioning-mapper; not for the beachhead''s beliefs and objections — use audience-belief-mapper; not for SERP keyword targeting — use keyword-research; not for claim adjudication — use offer-claims-registry. 品类叙事/竞争叙事拆解/语言惯例/叙事演变

Source

  • Repo: https://github.com/aaron-he-zhu/aaron-marketing-skills
  • Path: narrative/trace/category-narrative-mapper

Evaluation

AI-evaluated 2026-09-03: Thorough per-competitor teardown methodology with drift comparison via archived copy, Measured/User-provided/Estimated labeling, and robots pre-flight on scrapes. Depends on repo-local connector scripts (firecrawl/tavily/wayback) and the suite registries, which raises setup cost for anyone outside the ecosystem.

Score breakdown

Quality
8.0
Usability
5.0
Security
7.0
Popularity
7.0