discovery-interview-prep は何をしますか？
適切な目標、セグメント、制約、方法を用いてカスタマーディスカバリーインタビューを計画します。問題のバリデーション、チャーン調査、新製品アイデアのためのインタビュー準備に使用します。
カスタマーディスカバリーインタビューの計画を支援します。適切な目標、セグメント、制約、方法を設定し、問題のバリデーション、チャーン調査、新製品アイデアのためのインタビュー準備に使用します。
このスキルは、カスタマーディスカバリーインタビューを体系的に計画するためのものです。ユーザーがインタビューの目標（問題検証、チャーン調査、新製品アイデアなど）を設定し、適切な顧客セグメントを選定し、時間やリソースの制約を定義した上で、最適なインタビュー手法（構造化インタビュー、半構造化インタビュー、非構造化インタビューなど）を提案します。これにより、顧客のニーズや問題点を効率的に深掘りし、仮説検証を促進します。主にAIエージェントと連携して利用され、開発者やプロダクトマネージャーが顧客理解を強化する際に役立ちます。スキルのドキュメントは、目標設定からインタビュー実施までの一連のステップをガイドします。
npx skills add https://github.com/deanpeters/product-manager-skills/tree/main/skills/discovery-interview-prepInstalled? Explore more 研究＆データ分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
適切な目標、セグメント、制約、方法を用いてカスタマーディスカバリーインタビューを計画します。問題のバリデーション、チャーン調査、新製品アイデアのためのインタビュー準備に使用します。
This repo contains 20 individual skills — each has its own dedicated page.
Evaluate acquisition channels using unit economics, customer quality, and scalability. Use when deciding whether to scale, test, or kill a growth channel.
Assess whether your product work is AI-first or AI-shaped. Use when evaluating AI maturity and choosing the next team capability to build.
Understand the PM-to-Director transition through altitude and horizon thinking. Use when diagnosing scope, time-horizon, or leadership-level gaps.
Diagnose SaaS business health across growth, retention, efficiency, and capital. Use when preparing a business review or prioritizing urgent fixes.
Create a company research brief with executive quotes, product strategy, and org context. Use when preparing for interviews, competitive analysis, partnerships, or market-entry work.
Diagnose context stuffing vs. context engineering. Use when an AI workflow feels bloated, brittle, or hard to steer reliably.
Create a customer journey map across stages, touchpoints, actions, emotions, and metrics. Use when diagnosing a broken experience or aligning a team on the full customer flow.
Run a customer journey mapping workshop with adaptive questions and outputs. Use when you need to map stages, actions, emotions, pain points, and opportunities for a persona and scenario.
Guide the PM-to-Director transition across preparing, interviewing, landing, and recalibrating. Use when leadership scope is changing and you need practical coaching.
Run a full discovery cycle from problem hypothesis to validated solution. Use when a team needs a structured path through framing, interviews, synthesis, and experiments.
Write a clear, empathetic EOL announcement with rationale, customer impact, and next steps. Use when retiring a product, feature, or plan without creating avoidable confusion.
Break down epics into user stories with Humanizing Work split patterns. Use when a backlog item is too large to estimate, sequence, or deliver safely.
Frame an epic as a testable hypothesis with target user, expected outcome, and validation method. Use when defining a major initiative before roadmap, discovery, or delivery planning.
Plan a VP or CPO 30-60-90 day diagnostic onboarding path. Use when entering a new executive product role and avoiding premature change.
Evaluate feature investments using revenue impact, cost structure, ROI, and strategy. Use when deciding whether a feature deserves investment.
Evaluate pricing changes using ARPU, conversion, churn risk, NRR, and payback. Use when deciding whether a pricing move should ship.
Look up SaaS finance metrics, formulas, and benchmarks fast. Use when you need a quick metric definition, formula, or benchmark during analysis.
Uncover customer jobs, pains, and gains in a structured JTBD format. Use when clarifying unmet needs, repositioning a product, or improving discovery and messaging.
Guide teams through Lean UX Canvas v2. Use when framing a business problem, surfacing assumptions, and defining what to learn next.
Build an Opportunity Solution Tree from outcomes to opportunities, solutions, and tests. Use when a stakeholder request needs problem framing before you decide what to build.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.