Agent skill · product strategy · sundial-org

jtbd-analyzer

Uncover the real "job" customers hire your product to do. Goes beyond features to understand functional, emotional, and social motivations. Use when user says "jobs to be done", "jtbd", "why do customers", "what job", "customer motivation", "what problem", "user needs", "why do people buy".

Why this skill is useful

Provides a structured framework for understanding customer motivations and job dimensions that the AI wouldn't generate on its own.

What it needs

About 1k tokens when loaded. Last updated 2026-03-07. 639 stars on the source repository.

What this skill does

Jobs-To-Be-Done Analyzer The Core Concept Customers don't buy products. They HIRE products to do a job. "People don't want a quarter-inch drill. They want a quarter-inch hole." Actually: They want a shelf → to display photos → to feel proud of family. The Three Job Dimensions Dimension Question Format ----------- ---------- -------- Functional What task needs doing? "Help me [verb] [object]" Emotional How do I want to feel? "Make me feel [emotion]" Social How do I want to be seen? "Help me be seen as [quality]" The Process 1. Job Statement: "When [situation], I want to [motivation], so I can [outcome]" 2. Map all 3 dimensions for each user type 3. Find real competition: What ELSE could do this job? 4. Prioritize: Which jobs are most critical and underserved? Output Format Key Questions 1. "What were you trying to accomplish when you [action]?" 2. "Walk me through the last time you needed to [job]" 3. "What would you do if [product] didn't exist?" 4. "What's frustrating about how you currently [job]?" Integration Compounds with: first-principles-decomposer → Decompose job to atomic need cross-pollination-engine → Find how others solve similar jobs app-planning-skill → Use JTBD to inform features --- See references/examples.md for Artem-specific JTBD analyses

How to use it

Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:

@skills sundial-org/jtbd-analyzer

View the source on GitHub

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