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UsermuseUsermuse/em-plugin/skills/interview-script/SKILL.md

interview-script

Skill0 starsChanged 3 months agoMITView on GitHub

Write a Mom-Test customer interview guide — warm-up, JTBD exploration, wrap-up — but first check the evidence for what's ALREADY known so the questions target the open gaps instead of re-asking answered questions. Use when the user asks to 'write an interview script', 'prep for a user interview', 'discovery interview questions', 'interview guide', 'what should I ask customers', or 'plan a research call'. Trigger terms: interview script, interview guide, user interview, discovery interview, customer interview questions, Mom Test, research questions to ask. Not for summarizing an interview already done (that's summarize-conversation).

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The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 10 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Required — one parallel batch of searches: Verify the product (Rule 1), then fire in a single parallel batch:

    line 30
  2. Distinctive:

    Mom-Test rules: ask about their life not your idea · the past not the future · talk less (80/20) · never pitch · hunt for strong emotion · …

    line 58

“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Customer Interview Script (targeted at the gaps)

A Mom-Test interview guide — ask about their life, not your idea; the past, not the future. The Evermuse difference: before writing a single question, check what the corpus already answers. No point spending a scarce interview slot re-asking what six customers already told you. The script targets the open gaps, so each call buys new knowledge instead of confirming old.

Step 0 — Relevance & availability

Confirm this is interview prep and Evermuse is connected (see using-evermuse Step 0). If disconnected, you can still produce a solid Mom-Test script from the framework — label it ⚠ ungrounded and note you couldn't check what's already known, so it may re-ask settled questions.

Evermuse Grounding (required)

Follow ${CLAUDE_PLUGIN_ROOT}/skills/using-evermuse/SKILL.md.

Required — one parallel batch of searches. Verify the product (Rule 1), then fire in a single parallel batch:

  • 3–4 evidence searches, each worded from a different angle (limit up to 50). Evidence comes back rich and varied — expect large, useful result sets.
  • one guidance search and one context search (limit up to 50). These are usually sparse or empty; run them anyway and note when they're thin.

Read each response's digest — it reports how many more results exist. Use judgment on whether a query is worth pulling deeper (raise limit toward the 100 max and/or page with next_offset to avoid repeats), weighing payload size, remaining context, task complexity, and the value of the data. For deep pulls, consider spawning sub-agents — instruct them to return every citation with the same metadata the tools return (url, who_said_it, meeting_name, created_at) so you can still cite.

Optional — considered use. Once grounded, reach for the other tools only when they add value: a quote-angled search for verbatim voice, read_source for a single deep dive, inline citations (references/citations.md), and add_source to save the deliverable. Sources, citations, and saving are optional — not required.

Instructions

  1. Clarify research objectives. What decision will this research inform? What assumptions need validating?
  2. Split known vs. open (the key step). From the grounded evidence, list what the corpus already answers (with quotes) and what remains genuinely open. Write questions only for the open set; briefly show the user what you cut and why.
  3. Build the script — Mom-Test throughout:

    Opening (2–3 min): purpose is learning not selling; no right/wrong answers; permission to record; confirm time.

    Warm-up (5 min): role, typical day/week, how long they've done the relevant activity. Build rapport, understand context.

    Core exploration — JTBD (15–20 min), weighted to the open gaps:

    • Current behavior (past tense, specific): "Walk me through the last time you [did the thing]. What happened? What tools? How long? Who else?"
    • Pain points (observe, don't lead): "What was the hardest part? What have you tried? What happened?"
    • Desired outcomes (their words): "What does 'good' look like? How would you know it's working?"
    • Willingness to pay (skin in the game): "How much time/money does this cost you today? Have you looked for a better solution?"

    Probing: "Tell me more about that" · gentle "Why?" ×2–3 · "Can you give a specific example?" · "What happened next?" · "How did that make you feel?"

    Mom-Test rules: ask about their life not your idea · the past not the future · talk less (80/20) · never pitch · hunt for strong emotion · compliments are noise.

    Wrap-up (3–5 min): "Anything I didn't ask that matters?" · "Who else should I talk to?" · thanks · next steps.

  4. Note-taking template (include it):
    Participant: [Name / ID]   Date: [Date]
    Key Jobs: […]   Current Solution: […]
    Biggest Pain: […]   Desired Outcome: […]
    Willingness to Pay: […]   Surprise Finding: […]   Follow-up: […]

Deliverable

The script (with an up-front "Already known — not asking" box citing the corpus, and a "Targeting these gaps" list) plus the note-taking template. After the interview, hand off to /evermuse:summarize to feed the summary back into the corpus.


Further reading

  • Adapted from phuryn/pm-skills (MIT) — interview-script. Method: The Mom Test (Rob Fitzpatrick); Product Trio: Teresa Torres, Continuous Discovery Habits.

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