CtrlK
BlogDocsLog inGet started
Tessl Logo

buyer-persona-generator

Research a company's ideal customer profiles and build detailed synthetic buyer personas. Identifies 4-6 distinct buyer segments through web research, then creates rich, realistic personas with demographics, motivations, skepticism profiles, decision criteria, and language patterns. Use when you need to understand who your buyers are at a deep level — their motivations, objections, and how they evaluate solutions.

69

Quality

87%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

82%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-crafted instruction-only skill: highly actionable research queries and a complete persona template, a clearly phased workflow with a coverage checkpoint, and clean sectioning. The main improvement levers are moving the persona template to a reference file and trimming Tips-section redundancy with Phase 1.

Suggestions

Move the full persona JSON template (~55 lines) into a references/persona-template.json file and reference it from Phase 3, keeping only 2-3 key fields inline in SKILL.md.

Trim the Tips section — 'Research depth matters' and the specificity example largely restate Phase 1 and Phase 3 guidance; keep only the language-gap and skepticism tips, which add new rationale.

Add an explicit validation loop after Phase 2 (e.g., 'if fewer than 4 distinct segments emerge, broaden comparison and jobs searches before proceeding') to strengthen workflow checkpoints.

DimensionReasoningScore

Conciseness

Efficient overall — no explanations of concepts Claude already knows, and the persona JSON example is load-bearing as an output template. Minor trims possible: the Tips section partially restates Phase 1 research guidance, and the example carries some illustrative filler.

4 / 5

Actionability

Fully concrete: literal WebSearch queries ('[company] customers', '[company] vs', '[company] reviews'), a copy-paste-ready persona JSON template, attribute tables per segment, and explicit output file specs (personas.json, personas.md, segments.md). As an instruction-only skill, the guidance is specific and executable.

5 / 5

Workflow Clarity

Four clearly sequenced phases with a post-build checkpoint ('Coverage check — Confirm diversity rules are met') and defined output artifacts. No explicit validate-fix-retry loop, though the operations are non-destructive research and synthesis, so this is a minor gap rather than a cap.

4 / 5

Progressive Disclosure

Well-sectioned body with clear headers and no nested references; no bundle files exist. The ~55-line persona JSON template inlined in Phase 3 could arguably live in a references/ file, which is the main organization gap keeping it from 5.

4 / 5

Total

17

/

20

Passed

Description

88%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 strong description: concrete, third-person, comprehensive on capabilities, with an explicit 'Use when' trigger clause. The only gaps are a few missing natural synonyms (target audience, ICP) and modest overlap risk with general company-research requests.

DimensionReasoningScore

Specificity

Enumerates multiple concrete actions — 'Research a company's ideal customer profiles', 'Identifies 4-6 distinct buyer segments through web research', 'creates rich, realistic personas with demographics, motivations, skepticism profiles, decision criteria, and language patterns' — with comprehensive coverage of outputs in third-person voice.

5 / 5

Completeness

Explicitly answers both 'what' (research ICPs, identify 4-6 segments, build personas with named attributes) and 'when' ('Use when you need to understand who your buyers are at a deep level — their motivations, objections, and how they evaluate solutions') with concrete trigger phrasing.

5 / 5

Trigger Term Quality

Good natural keywords ('buyer personas', 'ideal customer profiles', 'buyer segments', 'motivations, objections') but a few common variations are missing, e.g. 'target audience', 'customer profile', or the 'ICP' acronym users often type.

4 / 5

Distinctiveness Conflict Risk

Persona synthesis from company research is a clear niche, but broad research-oriented triggers like 'research this company' or general marketing-analysis requests could overlap with related skills; not fully minimal conflict risk.

4 / 5

Total

18

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.