Structured discovery interview planning with adaptive methodology selection based on research goals and constraints.
Works with
Guides product managers through four adaptive questions to define research goals, target segments, access constraints, and interview methodology
Generates tailored interview frameworks with 5+ context-specific questions, follow-ups, and bias-avoidance guidance for each methodology (Mom Test, Jobs-to-be-Done, switch interviews, timeline mapping)
Includes opening/closing
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondiscovery-interview-prepExecute the skills CLI command in your project's root directory to begin installation:
Fetches discovery-interview-prep from deanpeters/product-manager-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate discovery-interview-prep. Access via /discovery-interview-prep in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Guide product managers through preparing for customer discovery interviews by asking adaptive questions about research goals, customer segments, constraints, and methodologies. Use this to design effective interview plans, craft targeted questions, avoid common biases, and maximize learning from limited customer access—ensuring discovery interviews yield actionable insights rather than confirmation bias or surface-level feedback.
This is not a script generator—it's a strategic prep process that outputs a tailored interview plan with methodology, question framework, and success criteria.
An interactive process that:
Use workshop-facilitation as the default interaction protocol for this skill.
It defines:
Other (specify) when useful)This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic.
This interactive skill asks up to 4 adaptive questions, offering 3-4 enumerated options at each step.
Agent suggests:
Before we design your interview plan, let's gather context:
For Your Own Product (Existing or Planned):
For Investigating an Existing Problem:
If Exploring a New Problem Space:
You can paste this content directly, or we can proceed with a brief description.
Agent asks: "What's the primary goal of these discovery interviews? (What do you need to learn?)"
Offer 4 enumerated options:
Or describe your own research goal (be specific: what question are you trying to answer?).
User response: [Selection or custom]
Agent asks: "Who are you interviewing? (Be as specific as possible.)"
Offer 4 enumerated options (adapted based on Q1):
Example (if Q1 = Problem validation):
Or describe your specific target segment (role, company size, behaviors, demographics).
Adaptation tip: Use personas or customer segments from provided materials.
User response: [Selection or custom]
Agent asks: "What constraints are you working with for these interviews?"
Offer 4 enumerated options:
Or describe your specific constraints (budget, time, access, team capacity).
User response: [Selection or custom]
Agent asks: "Based on your goal ([Q1]), target segment ([Q2]), and constraints ([Q3]), here are recommended interview methodologies:"
Offer 3-4 enumerated options (context-aware based on Q1-Q3):
Example (if Q1 = Problem validation, Q2 = People who experience problem regularly, Q3 = Limited access):
Problem validation interviews (Mom Test style) — Ask about past behavior, not hypotheticals. Focus on: "Tell me about the last time you [experienced the problem]. What did you try? What happened?" (Best for: Validating if problem is real and painful)
Jobs-to-be-Done (JTBD) interviews — Focus on what customers are trying to accomplish, not what they want. Ask: "What were you trying to get done? What alternatives did you consider? What made you choose X?" (Best for: Understanding motivations and switching behavior)
Switch interviews — Interview customers who recently switched from a competitor or alternative. Ask: "What prompted you to look for a new solution? What was the 'push' away from the old tool? What 'pulled' you to try ours?" (Best for: Understanding competitive positioning and unmet needs)
Timeline/journey mapping interviews — Walk through their entire experience chronologically. Ask: "Walk me through the first time you encountered this problem. What happened next? How did you try to solve it?" (Best for: Uncovering full context and pain points)
Choose a number, combine approaches (e.g., '1 & 2'), or describe your own methodology.
Adaptation examples:
User response: [Selection or custom]
After collecting responses, the agent generates a tailored interview plan:
# Discovery Interview Plan
**Research Goal:** [From Q1]
**Target Segment:** [From Q2]
**Constraints:** [From Q3]
**Methodology:** [From Q4]
---
## Interview Framework
### Opening (5 minutes)
- **Build rapport:** "Thanks for taking the time. I'm [name], and I'm researching [problem space]. This isn't a sales call—I'm here to learn from your experience."
- **Set expectations:** "I'll ask about your experiences with [topic]. There are no right answers. Feel free to be honest—critical feedback is most helpful."
- **Get consent:** "Is it okay if I take notes / record this conversation?"
---
### Core Questions (30-40 minutes)
**Based on your methodology ([Q4]), here are suggested questions:**
#### [Methodology Name] Questions:
1. **[Question 1]** — [Rationale for asking this]
- **Follow-up:** [Dig deeper with...]
- **Avoid:** [Don't ask leading version like...]
2. **[Question 2]** — [Rationale]
- **Follow-up:** [...]
- **Avoid:** [...]
3. **[Question 3]** — [Rationale]
- **Follow-up:** [...]
- **Avoid:** [...]
4. **[Question 4]** — [Rationale]
- **Follow-up:** [...]
- **Avoid:** [...]
5. **[Question 5]** — [Rationale]
- **Follow-up:** [...]
- **Avoid:** [...]
**Example (if Methodology = Problem validation - Mom Test style):**
1. **"Tell me about the last time you [experienced this problem]."** — Gets specific, recent behavior (not hypothetical)
- **Follow-up:** "What were you trying to accomplish? What made it hard? What did you try?"
- **Avoid:** "Would you use a tool that solves this?" (leading, hypothetical)
2. **"How do you currently handle [this problem]?"** — Reveals workarounds, alternatives, pain intensity
- **Follow-up:** "How much time/money does that take? What's frustrating about it?"
- **Avoid:** "Don't you think that's inefficient?" (leading)
3. **"Can you walk me through what you did step-by-step?"** — Uncovers details, edge cases, context
- **Follow-up:** "What happened next? Where did you get stuck?"
- **Avoid:** "Was it hard?" (yes/no question, not useful)
4. **"Have you tried other solutions for this?"** — Reveals competitive landscape, unmet needs
- **Follow-up:** "What did you like/dislike? Why did you stop using it?"
- **Avoid:** "Would you pay for a better solution?" (hypothetical)
5. **"If you had a magic wand, what would change?"** — Opens space for ideal outcomes (but treat with skepticism—focus on past behavior, not wishes)
- **Follow-up:** "Why does that matter to you? What would that enable?"
- **Avoid:** Taking feature requests literally
---
### Closing (5 minutes)
- **Summarize:** "Just to recap, I heard that [key insights]. Did I get that right?"
- **Ask for referrals:** "Do you know anyone else who experiences this problem? Could you introduce me?"
- **Thank them:** "This was incredibly helpful. I really appreciate your time."
---
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
discovery-interview-prep fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for discovery-interview-prep matched our evaluation — installs cleanly and behaves as described in the markdown.
We added discovery-interview-prep from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend discovery-interview-prep for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
discovery-interview-prep has been reliable in day-to-day use. Documentation quality is above average for community skills.
discovery-interview-prep reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added discovery-interview-prep from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for discovery-interview-prep matched our evaluation — installs cleanly and behaves as described in the markdown.
discovery-interview-prep fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
discovery-interview-prep reduced setup friction for our internal harness; good balance of opinion and flexibility.
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