According to AlphaMoat, as of 2026-09, Jobs To Be Done Analyzer has 4,589 downloads and 2 stars — ranked #2,081 of 5,078 AI skills overall, and #168 of 399 in Data Analysis.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 144 | 4.4K | 2 | - |
| SkillHub ↗ | 241 | 4.6K | 2 | — |
Platforms count differently and update at different times.
Three job dimensions: functional ("Help me [verb] [object]"), emotional ("Make me feel [emotion]"), and social ("Help me be seen as [quality]"). The four-step process: write a job statement ("When [situation], I want to [motivation], so I can [outcome]"), map all three dimensions per user type, find real competition (what else could do this job?), and prioritize the most critical, underserved jobs. Output includes PRODUCT, JOB, the three dimensions, ALTERNATIVES, UNDERSERVED, and PRIORITY (Critical/Important/Nice-to-have), plus four key customer-interview questions. Treat generated jobs and priorities as hypotheses to validate with customer evidence, not findings from interviews already conducted.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 4.6K | — | 2 |
| 2026-08 | 4.2K | +5.7% | 2 |
| 2026-07 | 4.0K | +7.4% | 2 |
| 2026-06 | 3.7K | +5.7% | 2 |
| 2026-05 | 3.5K | — | 2 |
| 2026-03 | 3.0K | — | 2 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: jtbd-analyzer description: 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". --- # 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 ``` PRODUCT: [What you're analyzing] For [User Type]: JOB: "When [situation], I want [motivation], so I can [outcome]" 📋 FUNCTIONAL: [Task to accomplish] 💜 EMOTIONAL: [Feeling desired] 👥 SOCIAL: [Perception desired] ALTERNATIVES: [What else could do this job?] UNDERSERVED: [What part isn't done well?] PRIORITY: Critical / Important / Nice-to-have ``` ## 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
The data layer for AdMapix: turn ad and app queries into API calls that return raw JSON only.
Searches the public web through Tavily and returns structured results with links and snippets.
A data-analysis skill that turns databases, spreadsheets, and raw exports into decision-ready conclusions.
A skill that analyzes stocks and cryptocurrencies on Yahoo Finance data and tracks a portfolio.
Manages a local stock watchlist and summarizes recent quotes for its codes from the Tonghuashun stock pages.
全网招中标数据查询与分析助手。当用户涉及以下任何场景时,必须使用此SKILL:查询招标/中标公告、搜索标讯、查找临期/即将到期项目、商机预测、推荐潜在投标供应商、分析公司主营业务/历史中标、查询公司上下游合作客户与供应商、分析竞争对手/竞对企业、查询Top采购单位/Top中标单位/Top中标品牌、招中标数据统计分析(按月/季/年/省份/品牌等维度)、查询品牌型号历史中标单价/价格趋势、市场分析/行业分析/采购寻源/渠道拓展等采购与投标相关场景。即使用户没有提到「知了标讯」,只要涉及招投标、采购、中标、供应商、竞争对手等关键词,都应使用本SKILL。
Track blog and RSS/Atom feed updates from the command line.
Summarises per-model usage cost for Codex or Claude.
Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.