| name | narrative-resonance-monitor |
| slug | aaron-narrative-resonance-monitor |
| displayName | Narrative Resonance Monitor · 叙事共鸣监测 |
| summary | 回声率/AI回答感知/份额之声/共鸣信号 |
| description | 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 |
| version | 20.1.0 |
| license | Apache-2.0 |
| compatibility | Claude Code and compatible agent-skill hosts |
| homepage | https://github.com/aaron-he-zhu/aaron-marketing-skills |
| when_to_use | Use in the TALE Evaluate phase to measure whether the durable narrative is resonating in the market: echo rate (market language overlap with the canon lexicon, method stated), AI-answer perception (how answer engines describe the brand vs the canon, tavily.py --answer, proxy-labeled), share-of-voice on a locked competitor panel (reusing share-of-voice-tracker), and public resonance signals via bluesky.py / gdelt.py / pageviews.py. The resonance-evidence feed for the E1 veto — every proxy number labeled proxy, never Measured. Not for scoring TALE profile result (that is narrative-quality-auditor) or own-site analytics (performance-monitor). |
| argument-hint | <brand / narrative> [canon lexicon path] [competitor panel] [platforms] |
| metadata | {"author":"aaron-he-zhu","version":"20.1.0","discipline":"narrative","phase":"evaluate","geo-relevance":"low","hermes":{"tags":["marketing","narrative","evaluate"],"category":"narrative"},"openclaw":{"emoji":"📖","homepage":"https://github.com/aaron-he-zhu/aaron-marketing-skills"}} |
Narrative Resonance Monitor
Measures whether the durable brand narrative is actually landing in the market — an echo rate (how much of the market's own language overlaps the narrative-registry canon lexicon, with the matching method declared), an AI-answer perception read (how answer engines describe the brand versus the canon, via scripts/connectors/tavily.py --answer, proxy-labeled), share-of-voice on a locked competitor panel, and public resonance signals from Bluesky / GDELT / Wikipedia-attention. It sits in the Evaluate phase of the TALE loop and is the resonance-evidence feed for the E dimension — specifically the upstream of the E1 evidence-integrity veto: the proxy-not-Measured discipline, echo-rate-with-declared-method, and AI-answer-perception sub-items (see tale-benchmark.md). It reads the canon lexicon but never edits it, and it never adjudicates a claim.
Scope guard: this skill produces the resonance report only. It does not rebuild share-of-voice tracking (it reuses share-of-voice-tracker — same locked-panel machinery, narrative/message query-term set swapped in), pull own-site GA4/GSC analytics (performance-monitor owns own-property telemetry), compute or cap the TALE profile result (narrative-quality-auditor is the sole gate), design the message tests whose results it later reads (message-test-designer), edit the canon lexicon (narrative-registry is the sole writer of memory/narrative-registry/), or adjudicate a claim (offer-claims-registry). It works one lever — resonance measurement — and hands off.
Quick Start
Measure narrative resonance for [brand] against our canon lexicon. Competitor panel: [list]. Platforms: [Bluesky / news / all keyless].
Run the AI-answer perception check: how do answer engines describe [brand] vs our positioning statement? Use tavily.py --answer and label it proxy.
