discovery-interview-prep

discovery-interview-prep is a skill for Claude Code, Codex from getcrew44/crew44. It costs 39 tokens per session (4,064 once invoked), scanned A, original, MIT.

A planning guide for customer discovery interviews, which are conversations used to learn about customers' problems, needs, or reasons for leaving. It helps choose a research method and prepare questions.

In plain words
What is it for?
Use it to plan interviews for validating a problem, researching customer churn, or exploring a new product idea, including the audience, questions, possible biases, and measures of success.
Why use it?
It reduces unfocused interviews, leading questions, and confirmation bias—the tendency to seek answers that support an existing idea. It also clarifies what the research should discover.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/getcrew44/crew44/discovery-interview-prep
Any agent
npx skills add getcrew44/crew44 --skill discovery-interview-prep
Clone the repo
git clone --depth 1 https://github.com/getcrew44/crew44

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for discovery-interview-prep

README.md
[![agentmods](https://agentmods.dev/badge/skills/getcrew44/crew44/discovery-interview-prep.svg)](https://agentmods.dev/skills/getcrew44/crew44/discovery-interview-prep)
Your own site
<a href="https://agentmods.dev/skills/getcrew44/crew44/discovery-interview-prep"><img src="https://agentmods.dev/badge/skills/getcrew44/crew44/discovery-interview-prep.svg" alt="Measured on agentmods" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,064 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.04064
Opus 5 $0.00019 $0.02032
Sonnet 5 $0.00008 $0.00813
Haiku 4.5 $0.00004 $0.00406

Measured 3d ago against content hash bb3b874041a6, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

discovery-interview-prep scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

daemon/internal/presets/defaultcrew/skills/product/discovery-interview-prep/SKILL.md · 411 lines

How it starts

The opening of the file, as written. The whole thing — 411 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

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.

Key Concepts

The Discovery Interview Prep Flow

An interactive process that:

  1. Gathers product/problem context (marketing materials, assumptions)
  2. Defines research goals (what you're trying to learn)
  3. Identifies target customer segment and access constraints
  4. Recommends interview methodology (Jobs-to-be-Done, problem validation, switch interviews, etc.)
  5. Generates interview framework with questions, biases to avoid, and success metrics

Why This Works

  • Goal-driven: Aligns interview approach to what you need to learn
  • Adaptive: Adjusts methodology based on product stage (idea vs. existing product) and access constraints
  • Bias-aware: Highlights common pitfalls (leading questions, confirmation bias, solution-first thinking)
  • Actionable: Outputs interview guide ready to use

Anti-Patterns (What This Is NOT)

  • Not a user testing script: Discovery = learning problems; testing = validating solutions
  • Not a sales demo: Don't pitch—listen and learn
  • Not surveys at scale: Deep qualitative interviews (5-10 people), not broad surveys (100+ people)

When to Use This

  • Starting product discovery (validating problem space)
  • Repositioning an existing product (understanding new market)
  • Investigating churn or drop-off (retention interviews)
  • Evaluating feature ideas before building
  • Preparing for customer development sprints

Read the full file on GitHub · 411 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 411 lines · 39 tokens per session scan A bb3b874041a6

Subscribe to this mod's changes

discovery-interview-prep is a skill published in the GitHub repository getcrew44/crew44 (359 stars, last pushed 2mo ago), licensed MIT. It adds 39 tokens to every session and 4,064 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.