audience-belief-mapper

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

Quality

80%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./narrative/trace/audience-belief-mapper/SKILL.md

Quality

Content

67%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-organized, actionable instruction skill with a clear sequenced workflow and good reference navigation. Its main drag is conciseness: the claims-routing clause and scope/handoff content repeat heavily across sections and could be defined once then referenced.

Suggestions

Define the 'route to memory/events/claims.ndjson via an authorized operation: propose request to registry-events.py' clause once (e.g. in Skill Contract) and refer back to it instead of repeating the full phrase in steps 3, 6, 7, Save Results, and the contract.

De-duplicate the scope-guard / handoff / TALE-dimension content that appears in both the opening paragraph and the Skill Contract section — keep one canonical statement and link to it.

Inline the handoff-summary and save-results templates (or a compact schema) rather than only referencing skill-contract.md, so the output format is actionable without an external file.

Dimension	Reasoning	Score
Conciseness	The body is instruction-dense with no basic-concept padding, but the clause 'via an authorized operation: propose request to registry-events.py' repeats verbatim 5+ times and the scope/handoff/claims-routing content recurs across the contract, instructions, and save sections, so it could be tightened substantially with a define-once pattern.	3 / 5
Actionability	Numbered steps name concrete file paths (memory/narrative/audience-belief-mapper/, memory/events/claims.ndjson), explicit labels (Measured/User-provided/Estimated), and output shapes (objections table, four-forces map); the exact handoff/save template is referenced externally rather than inlined, a minor gap.	4 / 5
Workflow Clarity	A clear 7-step sequence is anchored by an explicit 'Done when' checklist and a step-1 stop-and-route guard; the task is synthesis (non-destructive, ask-before-write) so the batch/destructive cap does not apply, though no explicit validate→fix→retry loop is present.	4 / 5
Progressive Disclosure	Clean section headers and clearly signaled, one-level-deep reference links (tale-benchmark.md, skill-contract.md, CONNECTORS.md, SECURITY.md, sibling skills) aid navigation, but no bundle ships with the skill and the referenced repo-level paths cannot be verified as real files.	4 / 5
	Total	15 / 20 Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A dense, well-structured description that concretely states what it produces and when to invoke it, with strong trigger phrasing and explicit disambiguation against sibling skills. Its only weakness is mild verbosity and a few missing synonym triggers.

Dimension	Reasoning	Score
Specificity	The description enumerates multiple concrete outputs — a belief map (held beliefs + mental models), a recurring-objections table with reframes, and the four named JTBD forces (push/pull/anxiety/habit) — plus sourcing labels and claims routing, giving comprehensive coverage.	5 / 5
Completeness	It explicitly answers both halves: 'Use when the user asks to...' supplies concrete when-triggers and 'produces a belief map of the beachhead — ...' supplies a concrete what.	5 / 5
Trigger Term Quality	Three natural quoted triggers a buyer would say ('map what our buyers believe', 'capture the objections we keep hearing', 'find the switching forces that move the beachhead') plus keywords like objections/switching/beachhead give good coverage, though a few synonyms (win-loss, mental models) appear only in the body.	4 / 5
Distinctiveness Conflict Risk	Explicit disambiguation ('Not for demographic or persona profiling — use audience-mapper; not for the positioning canvas — use positioning-truth-tracer') carves a clear niche with minimal conflict risk.	5 / 5
	Total	19 / 20 Passed

Validation

75%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 12 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_field	'metadata' should map string keys to string values	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
relative_links	Relative link issues: 27 suspicious	Warning
referenced_paths_exist	Referenced path issues: 2 missing, 2 deeper-than-1-level	Warning

	Total	12 / 16 Passed

Repository: aaron-he-zhu/aaron-marketing-skills
Path: narrative/trace/audience-belief-mapper/SKILL.md
Commit: 888dd38

Reviewed: 5 days ago

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