Atlas / Skills / aaron-he-zhu / Audience Belief Mapper

Audience Belief MapperSAFE

skills/aaron-he-zhu/audience-belief-mapper

120 marketing skills as an AI marketing staff — plugin, portable skills, or an 8-bot team across 7 disciplines (narrative, SEO/GEO, social, email, paid, influencer, launch) on one contract, with 8 auditor gates: TALE · CORE-EEAT · CITE · ECHO · SEND · ROAS · STAR · RAMP.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
20.1.0
Hosts
2 documented
License
Apache-2.0
Stars
3,014
01

Overview

120 marketing skills as an AI marketing staff — plugin, portable skills, or an 8-bot team across 7 disciplines (narrative, SEO/GEO, social, email, paid, influencer, launch) on one contract, with 8 auditor gates: TALE · CORE-EEAT · CITE · ECHO · SEND · ROAS · STAR · RAMP.

Read from source at commit 0b6ddc535651OBSERVED · 2026-10-26
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02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
claude-codementioned
openclawmentioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: audience-belief-mapper
slug: aaron-audience-belief-mapper
displayName: "Audience Belief Mapper · 受众信念图"
summary: "受众信念/异议/切换四力/流失语言"
description: 'Use when the user asks to "map what our buyers believe", "capture the objections we keep hearing", or "find the switching forces that move the beachhead"; produces a belief map of the beachhead — held beliefs and mental models, the recurring objections and their reframes, and the JTBD four forces (push of the problem, pull of the new, anxiety of switching, habit of the present) — each item sourced from interviews or win-loss notes (User-provided) and labeled Measured / User-provided / Estimated, with any unverified quote or comparative claim marked "[needs source]" and routed to the claims candidates, never adjudicated here. Not for demographic or persona profiling — use audience-mapper; not for the positioning canvas — use positioning-truth-tracer. 受众信念/异议地图/切换四力/流失语言'
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 when gathering the beachhead's narrative raw material before any brand narrative is authored: the beliefs and mental models buyers already hold, the objections they raise and how to reframe each, and the JTBD four forces (push / pull / anxiety / habit) that govern switching. The third move of the TALE Trace phase; feeds beachhead truth (T), objection reframes (A), and win-loss language (E). Not demographic persona profiling and not the positioning canvas."
argument-hint: "<product / beachhead> [interview / win-loss notes] [known objections]"
metadata: {"author": "aaron-he-zhu", "version": "20.1.0", "discipline": "narrative", "phase": "trace", "geo-relevance": "low", "hermes": {"tags": ["marketing", "narrative", "trace"], "category": "narrative"}, "openclaw": {"emoji": "📖", "homepage": "https://github.com/aaron-he-zhu/aaron-marketing-skills"}}
---

# Audience Belief Mapper

Captures the beachhead's narrative raw material — the beliefs and mental models buyers already hold, the objections that recur in every deal, each objection's reframe, and the JTBD **four forces** (push of the problem, pull of the new solution, anxiety of the switch, habit of the status quo) that decide whether they move. It is the third move of the TALE **Trace** phase and its output feeds three [TALE](../../../references/tale-benchmark.md) dimensions: **T** (beachhead/ICP truth — the narrative targets a segment scored on serviceability / pain / reachability, not "everyone"), **A** (the objection reframes the message house answers), and **E** (win-loss and objection language written back to the canon candidates). It never scores TALE profile result and never adjudicates a claim — unverified quotes or comparative statements are marked `[needs source]` and routed to `memory/events/claims.ndjson` via an authorized `operation: propose` request to `registry-events.py`.

**Scope guard**: this skill maps *beliefs, objections, and switching forces* only. It does **not** build demographic or firmographic persona profiles (reuse [audience-mapper](../../../influencer/scout/audience-mapper/SKILL.md) — this skill takes the persona base from there and does not rebuild it), reconcile the positioning canvas against shippable reality ([positioning-truth-tracer](../positioning-truth-tracer/SKILL.md)), build the change-narrative arc ([strategic-narrative-designer](../../architect/strategic-narrative-designer/SKILL.md)), adjudicate any claim ([offer-claims-registry](../../../protocol/offer-claims-registry/SKILL.md) is the sole writer of `memory/claims/claims-ledger.md`), or compute the TALE profile result (only the [narrative-quality-auditor](../../evaluate/narrative-quality-auditor/SKILL.md) gate scores TALE). It works one lever — audience belief — and hands off.

## Quick Start

```
Map the beliefs, objections, and switching forces for [product]'s beachhead. Here are [N] interview / win-loss notes: [paste].
```

```
Turn these lost-deal reasons into the JTBD four forces (push / pull / anxiety / habit) and a reframe for each objection: [paste].
```

```
We keep hearing "[objection]" — capture it, source it to the interviews, and draft the reframe candidates.
```

## Skill Contract

**Expected output**: a belief map for the beachhead — held beliefs / mental models, a recurring-objections table (objection · frequency-source · reframe candidate), and the JTBD four-forces map (push / pull / anxiety / habit, each with the evidence line it came from) — every item labeled Measured / User-provided / Estimated, plus a `[needs source]` list for any unverified quote or comparative claim, and the standard handoff summary.

- **Reads**: interview transcripts, win-loss notes, sales-call summaries, and support tickets (all User-provided); the persona base from [audience-mapper](../../../influencer/scout/audience-mapper/SKILL.md) output in `memory/influencer/audience-mapper/` when present; the claims ledger `memory/claims/claims-ledger.md` (read-only) to know which comparative statements are already approved.
- **Writes**: the belief/objection/forces map to `memory/narrative/audience-belief-mapper/`; every unverified quote or comparative claim marked `[needs source]` to `memory/events/claims.ndjson` via an authorized `operation: propose` request to `registry-events.py` (this skill never adjudicates); a durable, canon-grade belief or reframe surfaces only to `memory/events/narrative.ndjson` via an authorized `operation: propose` request to `registry-events.py` — [narrative-registry](../../../protocol/narrative-registry/SKILL.md) is the sole writer of `memory/narrative-registry/` canon files.
- **Promotes**: the top objections and their reframes, plus the dominant switching force, to `memory/hot-cache.md` and `memory/open-loops.md` (ask before writing); never writes `decisions.md` directly.
- **Done when**: every belief, objection, and force is traced t
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-26 · audit v0.4.1 · source sha 0b6ddc535651full audit observations/trust-audit/skill/aaron-he-zhu__audience-belief-mapper.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-260b6ddc535651SAFEB89first audit
06

Questions

What does the audience-belief-mapper — aaron-he-zhu/aaron-marketing-skills skill do?

120 marketing skills as an AI marketing staff — plugin, portable skills, or an 8-bot team across 7 disciplines (narrative, SEO/GEO, social, email, paid, influencer, launch) on one contract, with 8 auditor gates: TALE · CORE-EEAT · CITE · ECHO · SEND · ROAS · STAR · RAMP.

Is audience-belief-mapper — aaron-he-zhu/aaron-marketing-skills safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can audience-belief-mapper — aaron-he-zhu/aaron-marketing-skills access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does audience-belief-mapper — aaron-he-zhu/aaron-marketing-skills work with?

Its documentation mentions claude-code and openclaw. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (0b6ddc535651), read on 2026-10-26. The repository is watched, and a new audit runs when it changes — this is the first audit.

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