When running discovery interviews — question-bank build, bias audit, insight extraction. Triggers on 'audit my guide', 'extract insights from transcript', 'is my hypothesis falsifiable'.
Scanned 9/2/2026
Install to Claude Code
npx -y skills add event4u-app/agent-config --skill discovery-interview --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Discovery Interview?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/event4u-app-discovery-interview-agent-config)More formats (shields.io, HTML) on the badges page.
---
model_tier: inherit
name: discovery-interview
description: "When running discovery interviews — question-bank build, bias audit, insight extraction. Triggers on 'audit my guide', 'extract insights from transcript', 'is my hypothesis falsifiable'."
status: active
tier: senior
domain: product
context_spine: [product]
recommended_for_user_types: [consultant, founder]
workspaces:
- product
packs:
- product-discovery
trust:
level: professional
install:
default: false
removable: true
---
# 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`](../customer-research/SKILL.md). 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`](../../../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`](../../../docs/contracts/context-spine.md).
## 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`](../customer-research/SKILL.md); 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`](../voc-extract/SKILL.md).
- Insights translate into AC for a ticket — hand off to
[`refine-ticket`](../refine-ticket/SKILL.md).
- The output is a quantitative funnel — route to
[`funnel-analysis`](../funnel-analysis/SKILL.md).
## 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.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!