Audience Belief Mapper
Turn interview and win-loss evidence into a beachhead belief, objection, and switching-forces map.
The skill treats interviews and scraped material as untrusted data, limits inputs to user-provided evidence, requires beachhead confirmation, and routes claims through authorized propose events rather than direct canonical writes. It also asks for confirmation before saving or promoting memory. Deducted 7 points because handling of sensitive interview or support data lacks explicit redaction, retention, and access-control rules, and rollback is not fully specified in this skill.
Instructions, inputs, outputs, completion criteria, and termination rules are comparatively explicit, including a stop-and-route behavior when persona evidence is missing. Deducted 12 points because this static review found no skill-specific tests or real failure-run evidence covering key paths; authorized writes, referenced paths, and host capabilities introduce environment-dependent failure modes.
Triggers, audience, input materials, output shape, and non-fit boundaries are clear. Core operation does not require overseas connectors, and Chinese labels and metadata are present. Deducted 4 points because handling of missing interviews, conflicting evidence, very small samples, and non-English material is not sufficiently defined; mainland-China reachability is supported mainly by manual input rather than demonstrated environment validation.
The skill includes versioning, Apache-2.0 licensing, quick starts, contract, data sources, instructions, references, handoff, next-skill guidance, and limitation disclosures; the README adds installation and architecture context. Deducted 5 points because there is no skill-specific changelog, clearly assigned maintenance owner, or update path; README and SECURITY contain a version-line inconsistency between 18.0.0 and supported 17.x; the handoff format depends on an external reference not supplied here.
The expected deliverable is concrete: a belief map, objection-and-reframe table, JTBD four-forces map, evidence lines, labels, and needs-source list, suitable for downstream narrative work. Deducted 9 points because no representative output or third-party execution evidence is included; usefulness depends heavily on complete user-provided notes and an existing persona base, while reframes still require later review.
The skill requires evidence-line tracing, verbatim language, Measured/User-provided/Estimated separation, and needs-source routing for unverified claims, providing some auditability. Deducted 6 points because evidence remains primarily user-supplied, with no independent corroboration, fixed examples, skill-specific tests, or third-party results; repository tests cover shared architecture and artifact validation, not this skill's key paths.
- Do not treat Estimated reframes or user quotations as verified facts; comparative and product claims require later registry review.
- Confirm authorization for persona, interview, and win-loss materials, and redact personal or sensitive commercial information before processing.
- Verify that the host supports registry-events.py, the required memory paths, and authorization capabilities; otherwise produce a draft only and do not write.
- Note the inconsistency between the README's 18.0.0 version and SECURITY.md's statement that 17.x is the supported line.
What does this skill do, and when should you use it?
Audience Belief Mapper is a Narrative / Trace skill in Aaron Marketing Skills. It focuses on a defined beachhead and organizes buyers’ existing beliefs and mental models, recurring objections with reframe candidates, and the JTBD forces behind switching: push, pull, anxiety, and habit. Each item is tied to user-provided evidence and labeled Measured, User-provided, or Estimated. It is a fit for teams preparing brand narrative work, but it does not build personas, reconcile positioning, adjudicate claims, or score TALE.
It reads user-provided interview transcripts, win-loss notes, sales-call summaries, and support tickets, plus an audience-mapper persona base and read-only claims ledger when available. It extracts buyer beliefs and verbatim language, builds an objection / frequency-source / reframe-candidate table, maps evidence to push, pull, anxiety, and habit, and marks unverified quotes or comparative statements as “[needs source]”. It produces a belief map, four-forces map, open-source-needed list, and standard handoff summary; with authorization, it can also save working memory or submit registry-event proposals.
- A product marketing team has interview notes and wants to understand how its beachhead views the problem and available alternatives.
- A sales team is reviewing lost deals and needs to separate the forces that create urgency from the forces that preserve the status quo.
- A brand narrative team keeps hearing the same objection and wants to preserve the buyer’s wording while drafting reframe candidates.
- A research team wants to synthesize support-ticket concerns into raw material for narrative development.
What are this skill's strengths and limitations?
- Provides a concrete structure covering beliefs, objection reframes, and all four JTBD switching forces.
- Requires each item to be tied to specific evidence and labeled by evidence status.
- Preserves verbatim win-loss language and flags unsupported quotes or comparisons.
- Has a defined handoff to strategic-narrative-designer and the shared narrative registry workflow.
- Depends on user-provided interviews, win-loss notes, or comparable qualitative evidence.
- Stops when the audience-mapper persona base is missing.
- Does not handle demographic or firmographic profiling, positioning reconciliation, claim adjudication, or TALE scoring.
- Public review language is limited to excerpts the user provides; optional connector retrieval is labeled proxy rather than Measured.
How do you install this skill?
Install the collection in Claude Code with /plugin marketplace add aaron-he-zhu/aaron-marketing-skills, then /plugin install aaron-marketing@aaron. On an Agent Skills-compatible host, run npx skills add aaron-he-zhu/aaron-marketing-skills, or clone https://github.com/aaron-he-zhu/aaron-marketing-skills. The skill file is narrative/trace/audience-belief-mapper/SKILL.md.
How do you use this skill?
Confirm the target beachhead, then provide interview or win-loss evidence. Example: Map the beliefs, objections, and switching forces for [product]'s beachhead. Here are [N] interview / win-loss notes: [paste]. If the persona base is missing, the skill routes to audience-mapper before mapping beliefs for a segment.
How does this skill compare with similar options?
Compared with audience-mapper, this skill focuses on beliefs, objections, and switching forces rather than demographic or firmographic profiling. Compared with positioning-truth-tracer, it does not reconcile a positioning canvas against shippable reality.