vaibhav0806/startup-skill-pack · Archived

customer-discovery

Design and synthesize customer interviews, problem research, evidence ledgers, and validation experiments.

First seen Aug 19, 2026

Installation

$ npx skills add vaibhav0806/startup-skill-pack --skill customer-discovery

Summary

  • Design and synthesize customer interviews, problem research, evidence ledgers, and validation experiments.
  • Use when founders need to learn whether a real customer has an urgent problem or test a risky assumption; do not use it to manufacture testimonials, pitch during research, or replace product analytics.

Stronger alternatives

This repository is archived — consider an actively maintained alternative.

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from vaibhav0806/startup-skill-pack · top by installs.

npx skills add vaibhav0806/startup-skill-pack

Browse all from vaibhav0806/startup-skill-pack

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

License LICENSE
Default branch main
Open issues 0
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,121 B
  • docs SUMMARY.md 334 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Customer Discovery

Produce decision-grade evidence, not a list of agreeable quotes.

Workflow

  1. State the decision and the riskiest assumption it depends on.
  2. Define the target participant and disqualifiers before recruiting.
  3. Read [interviews.md](references/interviews.md) to prepare or conduct interviews.
  4. Read [evidence-synthesis.md](references/evidence-synthesis.md) to combine notes without losing contradictions or source context.
  5. Read [validation-experiments.md](references/validation-experiments.md) when interviews alone cannot test the assumption strongly enough.
  6. Return what is observed, inferred, proposed, stale, or conflicting; the strongest disconfirming evidence; confidence; and the next decision.

Boundaries

  • Ask about recent behavior, actual workflow, triggers, attempted solutions, cost, and authority. Hypothetical willingness and compliments are weak evidence.
  • Do not pitch during a discovery interview or teach the participant the desired answer.
  • Route market, ICP, business-model, or resource-allocation choices to startup-strategy after evidence exists.
  • Route measurement design, funnels, cohorts, and retention proof to startup-metrics.
  • Minimize personal data. Work in three explicit stages: (1) anonymous criteria and source planning; (2) compiling identifiable prospects; (3) outbound contact. Obtain scoped authorization before stages 2 and 3. Stage 2 authorization must cover target population, permitted source systems, data fields, storage/access, and retention. Stage 3 authorization must cover the exact population, channel, message, incentive, recording, retention, and note sharing. An imperative such as “find and message” does not waive the immediately-before-action check.