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event4u-app/agent-config/src/skills/discovery-interview/SKILL.md

discovery-interview

Use when running discovery interviews — question-bank build, bias audit, insight extraction. Triggers on 'audit my guide', 'extract insights from transcript', 'is my hypothesis falsifiable'.

Source repository stars
7
Declared platforms
0
Static risk flags
0
Last source update
2026-08-04
Source checked
2026-08-04

Decision brief

What it does—and where it fits

Triggers on 'audit my guide', 'extract insights from transcript', 'is my hypothesis falsifiable'.

Best for

  • A discovery slice has been framed (customer-research ran), but the interview guide is still rough or untested.
  • A transcript exists and the team needs structured insight extraction, not narrative summary.
  • An interview round produced surprising findings; a bias audit is needed before the team acts on them.

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/event4u-app/agent-config --skill "src/skills/discovery-interview"
Safe inspection promptEditorial

Inspect the Agent Skill "discovery-interview" from https://github.com/event4u-app/agent-config/blob/798a65522c7a73b90526641d6d1589fe0937cb5f/src/skills/discovery-interview/SKILL.md at commit 798a65522c7a73b90526641d6d1589fe0937cb5f. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Procedure

    1. Anchor on the switch event from customer-research. The first question is always "Walk me through the day you decided to ..." — never "would you ...". 2. Three layers: - Past behaviour (what did you do? when? alternative considered?) - Anxiety / habit (what feared in switching…

    Anchor on the switch event from customer-research. TheThree layers:Past behaviour (what did you do? when? alternative considered?)
  2. 02

    When to use

    Do NOT use for the upstream framing of the discovery slice (frame sentence, recruit criteria, JTBD focal job) — that is customer-research. Do NOT use for quantitative survey design or scale-bound research.

    A discovery slice has been framed (customer-research ran), but the interview guide is still rough or untested.A transcript exists and the team needs structured insight extraction, not narrative summary.An interview round produced surprising findings; a bias audit is needed before the team acts on them.
  3. 03

    Cognition cluster

    Mental model 22 — Data-informed, not data-driven. Interview

    Mental model 22 — Data-informed, not data-driven. InterviewMental model 15 — Signal vs noise. A vivid quote from oneMental model 28 — Eisenhower matrix. Sort post-interview
  4. 04

    1. Build the question bank

    1. Anchor on the switch event from customer-research. The first question is always "Walk me through the day you decided to ..." — never "would you ...". 2. Three layers: - Past behaviour (what did you do? when? alternative considered?) - Anxiety / habit (what feared in switching…

    Anchor on the switch event from customer-research. TheThree layers:Past behaviour (what did you do? when? alternative considered?)
  5. 05

    2. Audit the bank for bias

    Before running, inspect each question and review the bank against the four common biases:

    Leading — "Don't you think X is annoying?" → rewrite as pastHypothetical — "Would you use Y?" → replace with "LastConfirmation — every question presupposes the team's hypothesis

Permission review

Static risk signals and limitations

No configured static risk pattern was detected

This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score85/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars7SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
event4u-app/agent-config
Skill path
src/skills/discovery-interview/SKILL.md
Commit
798a65522c7a73b90526641d6d1589fe0937cb5f
License
MIT
Collected
2026-08-04
Default branch
main
View the original SKILL.md

discovery-interview

When to use

  • A discovery slice has been framed (customer-research ran), but the interview guide is still rough or untested.
  • A transcript exists and the team needs structured insight extraction, not narrative summary.
  • An interview round produced surprising findings; a bias audit is needed before the team acts on them.

Do NOT use for the upstream framing of the discovery slice (frame sentence, recruit criteria, JTBD focal job) — that is customer-research. Do NOT use for quantitative survey design or scale-bound research.

Cognition cluster

  • Mental model 22 — Data-informed, not data-driven. Interview data is signal at low N; treat it as evidence to reason with, not a vote count. See docs/contracts/mental-models.md § 22.
  • Mental model 15 — Signal vs noise. A vivid quote from one articulate user can swamp three muted but consistent signals; frequency-rank by distinct people, never by quote count. See mental-models.md § 15.
  • Mental model 28 — Eisenhower matrix. Sort post-interview insights into urgent / important quadrants so the team acts on high-importance signals, not the loudest ones. See mental-models.md § 28.
  • Product context-spine slot. Read product for the focal job
    • competitor names; do not re-derive these inside this skill. See context-spine.

Procedure

1. Build the question bank

  1. Anchor on the switch event from customer-research. The first question is always "Walk me through the day you decided to ..." — never "would you ...".
  2. Three layers:
    • Past behaviour (what did you do? when? alternative considered?)
    • Anxiety / habit (what feared in switching? what habit died?)
    • Outcome (what changed for you? expected? unexpected?)
  3. Cap at 8 open questions per 45-min slot. Beyond that, the interview becomes a survey delivered in person.

2. Audit the bank for bias

Before running, inspect each question and review the bank against the four common biases:

  • Leading"Don't you think X is annoying?" → rewrite as past behaviour.
  • Hypothetical"Would you use Y?" → replace with "Last time you needed Y, what did you do?".
  • Confirmation — every question presupposes the team's hypothesis is correct. At least two questions must be able to disconfirm it.
  • Recall ceiling — questions that ask for events ≥ 90 days back produce confabulation; bound the timeframe.

A bank that survives the audit unchanged is suspect — re-read.

3. Run-time discipline

  1. Open with the switch event. Stay silent for 8 seconds after the user finishes; the second answer is usually the truer one.
  2. Capture verbatim, not paraphrase. "It made me anxious" is data; "the user expressed concern" is interpretation.
  3. Probe with "tell me more about X" on any anxiety / habit mention; do not switch topics until the thread is exhausted.

4. Extract insights

For each transcript:

  1. One quote per insight. Tag: switch / anxiety / habit / expected-outcome / unexpected-outcome / disconfirmation.
  2. Frequency-rank by distinct interviewees (≥ 3 = signal; 1 = anecdote).
  3. Mark disconfirmations explicitly — these are the most valuable rows, because they are the cheapest to ignore.

5. Hand back

Produce the three artifacts (see ## Output); hand the disconfirmation log to whoever owns the original hypothesis.

Related Skills

WHEN to use this

  • The discovery slice is framed and the interview guide / transcript is the unit of work.
  • A round of interviews ran and the insights need structured extraction (frequency-ranked, bias-audited, disconfirmations highlighted).

WHEN NOT to use this

  • The slice itself is unframed — start with customer-research; this skill inherits its frame, never re-derives it.
  • The signal needs to come from existing artefacts (issues, PRs, errors) rather than a live interview — route to voc-extract.
  • Insights translate into AC for a ticket — hand off to refine-ticket.
  • The output is a quantitative funnel — route to funnel-analysis.

When the agent should load this

  • "Hilf mir den Interview-Leitfaden auditieren."
  • "Welche Fragen sind biased?"
  • "Extract die Insights aus diesem Transkript."
  • "Wir haben 6 Interviews geführt — was ist Signal, was ist Anekdote?"
  • "Ist meine Hypothese widerlegbar mit dem aktuellen Frageset?"

Output

  1. question-bank.md — 8 open questions, each tagged past-behaviour / anxiety-habit / outcome; bias-audit notes per rewritten question.
  2. insight-log.md — one row per insight: quote · interviewee ID · tag · distinct-people frequency. Sorted descending. Verbatim.
  3. disconfirmation-log.md — each row names the original hypothesis, the interview-derived disconfirmation, and the named owner who must respond before the team acts on the round.

Gotcha

  • A bank that survived the audit unchanged is rare; usually means the audit was rushed, not that the bank was perfect.
  • One articulate interviewee biases insight-extraction toward their vocabulary — frequency-rank by people, not quotes.
  • Disconfirmations are the cheapest insight to ignore and the most valuable to act on; the log exists so they survive the round.

Do NOT

  • Do NOT re-derive the frame inside this skill — read the product spine slot or hand back to customer-research.
  • Do NOT translate insights into AC inside this skill — that is refine-ticket.
  • Do NOT collapse disconfirmations into "we also heard X" prose; they earn their own log.

Alternatives

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