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Design a detailed value proposition using a 6-part JTBD template — Who, Why, What before, How, What after, Alternatives. Use when creating a value proposition, analyzing customer value delivery, or articulating why customers should choose your product.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
The method for finding the gap between what a system is supposed to do and what the code actually does — the class of bug generic scanners miss because they have no model of intent. Defines what counts as documented intent, what counts as implementation evidence, which mismatches matter, and how to avoid hand-wavy findings. Use when auditing AI-built code, reviewing access control against documented permissions, or checking whether a codebase matches its own documentation.
The durable documentation set that makes an AI-built (vibe-coded) app reviewable before shipping. A small core every app needs — architecture, user/permission flows, permissions, variables/secrets, and a test-coverage map — plus conditional docs added only when they apply: emails, scheduled work, SEO, and embedded agents/automation. Defines what each doc must capture and how a reviewer or auditor uses it. Use when documenting a codebase for handoff, mapping user journeys and trust-boundary crossings, planning test coverage, or preparing for a security or performance audit.
Red-team a PRD, roadmap, or strategy by attacking its load-bearing assumptions before reality does. Steelmans then attacks each claim, ranks failure modes by impact × likelihood × cheapness-to-test, and returns the cheapest test and kill criteria for each. Use when stress-testing a plan, pressure-testing a strategy, challenging assumptions, or preparing a doc for executive review.
Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.
Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring databases, or translating business questions into queries.
| name | value-proposition |
| description | Design a detailed value proposition using a 6-part JTBD template — Who, Why, What before, How, What after, Alternatives. Use when creating a value proposition, analyzing customer value delivery, or articulating why customers should choose your product. |
You are a product strategist designing a clear value proposition for $ARGUMENTS.
Your task is to develop a comprehensive value proposition that articulates the customer value delivered by the product.
1. Who
2. Why (Problem)
3. What Before
4. How (Solution)
5. What After
6. Alternatives
This template vs Strategyzer's Value Proposition Canvas: Strategyzer's canvas (by Alexander Osterwalder) is widely used but has structural limitations. This 6-part JTBD template (by Paweł Huryn and Aatir Abdul Rauf) addresses them:
Use Strategyzer's Value Proposition Canvas when you need a detailed pains/gains decomposition for a mature product with complex customer needs. Use this 6-part template for clarity, speed, and actionable output.
