Installation
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 "narrative-resonance-monitor" skill by following the instructions at https://skill123.me/install/narrative-resonance-monitor.
Run in your terminal — downloads and installs to ~/.claude/skills/.
curl -fsSL https://skill123.me/install/narrative-resonance-monitor.sh | bash
Download the zip and extract it into your skills directory (e.g. ~/.claude/skills/), then restart your session.
⬇ Download v1.0.0 · 5 KBAbout this skill
Overview
Use when the user asks to "measure how our narrative is landing", "track echo rate against our canon lexicon", or "check how AI answer engines describe our brand"; produces a resonance report — echo rate (overlap of market language with the narrative-registry canon lexicon, method declared), AI-answer perception via tavily.py --answer (proxy-labeled), share-of-voice on a locked competitor panel (reusing share-of-voice-tracker), and resonance signals from bluesky.py / gdelt.py / pageviews.py — every number labeled Measured / proxy / User-provided, feeding the TALE E dimension and the upstream of the E1 evidence-integrity veto. Not for rebuilding share-of-voice machinery — use share-of-voice-tracker; not for own-site GA4/GSC analytics — use performance-monitor; not for scoring TALE profile result — use narrative-quality-auditor; not for adjudicating claims — use offer-claims-registry. 回声率/AI回答感知/份额之声/共鸣信号
Source
- Repo: https://github.com/aaron-he-zhu/aaron-marketing-skills
- Path: narrative/evaluate/narrative-resonance-monitor
Evaluation
AI-evaluated 2026-09-03: Careful measurement discipline with declared echo-rate methods, proxy-vs-Measured labeling, locked panels, and closed-platform compliance boundaries; but the core task (canon lexicon echo rate, AI-answer perception vs a registry canon) is a niche suite-internal metric requiring canon and connectors to exist.