Jtbd switch interview
Modular agent skills for Jobs-to-be-Done and Outcome-Driven Innovation research.
npx -y skills add lishix520/jtbd-skills --skill jtbd-switch-interviewAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 14 days oldThe repository was created 14 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Interactive interview guide and question generator for understanding why customers change behaviors, buy products, or switch solutions. Use when asked to design a customer interview, formulate non-leading follow-up questions, reconstruct a decision timeline, or avoid leading feature questions during customer discovery. Do not use to define a Core Functional Job, calculate opportunity scores, or recommend product strategy.
SKILL.md
5.3 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it
JTBD Switch Interview Guide
Turn customer feedback into a discovery conversation that uncovers real reasons for buying, switching, or churning.
Use this when
- You have a customer quote, review, feedback fragment, or sales note and need to know what to ask next.
- You are planning a customer discovery interview and want to avoid asking leading questions.
- You want to uncover why a customer switched solutions, bought a competitor, or hesitated to sign up.
Don't use this when
- You need to map a complete 8-stage functional workflow (use
jtbd-job-mapper). - You have quantitative survey rating data and need Opportunity Scores (use
jtbd-opportunity-calculator). - You need to audit strategic pricing or growth positioning (use
jtbd-growth-strategist).
Minimum input
- Minimum Input: A single customer quote, a feedback statement, an interview transcript fragment, or a target customer behavior you want to investigate. (Can also run with zero input to generate an initial interview plan).
What you get
- One primary non-leading question to speak out loud.
- Why it matters in 2 simple sentences.
- A follow-up probe if the customer's answer is vague.
- ⚠️ What NOT to ask right now (avoiding feature traps and speculative questions).
- 📌 Current Understanding Summary (What is Known, What is Assumed, What is Missing).
- Structured Metadata for downstream methodology agents.
Quick prompt
"Help me choose the next interview question for this customer quote: '[Paste customer statement here]'."
What to do next
- Have customer notes/transcripts? Pass them to
jtbd-context-explorerto extract structured circumstances and constraints. - Want to analyze switching inertia vs push forces? Pass excerpts to
jtbd-forces-analyzer.
Scope & Three Interactive Modes
1. Starting Mode (No Input Provided)
- Identify target interviewee persona criteria.
- Formulate the first neutral, event-based opening question.
2. Single Quote Mode (Fragment / Feedback Input)
- Identify which phase of the decision timeline is missing (
first_thought,passive_looking,active_looking,decision,first_use,ongoing_use). - Output 1 Main Question, 1 Follow-up Probe, 1 Forbidden Question (What NOT to Ask), and a Known / Assumed / Missing Summary.
3. Transcript Mode (Partial Transcript Input)
- Extract a chronological timeline summary.
- Identify unverified hypotheses and major evidence gaps.
- Output the single most critical next question for the subsequent interview round.
Core Interviewing Discipline
- Ask About Past Behavior, Not Future Speculation: Ask "When was the last time you..." rather than "Would you buy...".
- One Question at a Time: Never overload the interviewer with long lists of questions. Output exactly ONE primary question.
- Never Lead With Solution Features: If a customer mentions a feature request (e.g., "I want a Jira button"), redirect to the triggering event and current approach.
- Isolate Specific Events: Focus on concrete, anchored moments in time (who was there, what happened, when it failed).
- Human-First Conversational Output: Always render a clean, human-readable interview guide first, followed by structured metadata for downstream agents.
Default Output Format (Human-First UX)
## 💬 What to Ask Next
"[Primary non-leading question to speak out loud]"
### Why This Question Matters
[Brief 2-sentence explanation of what timeline gap or hypothesis this question investigates.]
### If the Answer Is Vague
"[Concrete follow-up probe asking for specific past details or events]"
### ⚠️ What NOT to Ask Right Now
"[Explicit warning against a specific leading question, feature discussion, or speculative query]"
### 📌 Current Understanding Summary
- **What is Known**: [Direct evidence extracted from input]
- **What is Assumed**: [Interpretation or logical hypothesis]
- **What is Missing**: [Key evidence gap to investigate next]
---
### 📊 Structured Metadata (Agent Mode)
```yaml
analysis_status: plan_generated | evidence_extracted | insufficient_input
interview_focus: first_thought | passive_looking | active_looking | decision | first_use | ongoing_use | unknown
timeline_summary:
first_thought: ""
passive_looking: ""
active_looking: ""
decision: ""
first_use: ""
ongoing_use: ""
current_hypotheses:
- id: "HYP-001"
statement: ""
status: unverified
evidence_gaps:
- ""
next_question_type: event_anchor | push_trigger | current_workaround | alternative_evaluation | anxiety_probe | outcome_clarification
---
## Reference
Read `references/switch-interview-rules.md` before:
- Redirecting a feature request into a timeline event
- Formulating non-leading timeline questions
- Identifying the 6 phases of the decision timeline
- Distinguishing behavioral evidence from customer speculation