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synthetic-customer-discovery

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1GitHub TrendingGeneralby kdykes

Customer discovery with grounded synthetic personas. Plan interview studies, build evidence-grounded persona files, run synthetic discovery interviews against them, and synthesize transcripts (real or synthetic) into evidence-backed reports. Use when planning customer or user interviews, writing screeners or interview guides, building or refining personas or an ICP profile, pressure-testing positioning or pricing hypotheses before talking to real people, or synthesizing interview transcripts. Synthetic output is always framed as hypothesis, never as validation.

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Overview

Synthetic Customer Discovery

End-to-end customer discovery with the methodological craft of a professional research shop, plus a synthetic-interview engine that runs on hand-built, grounded personas instead of a one-line profile string.

Design stance

  • Synthetic output is a hypothesis, never a verdict. Every synthetic run is explicitly

framed as a hypothesis generator. The required next step is validation against real participants. This is the documented mitigation for persona collapse, the failure mode where an LLM asked to play "a customer" flattens to the average internet idea of one.

  • Persona depth does the work. Personas are structured artifacts grounded in specific lived

episodes from real people the user has access to (themselves, customers, support tickets, sales calls), not demographic strings.

  • Local and transparent. Interviews run inside the conversation against a readable persona

file. No paid black-box backend. The user can see, version, and correct every persona.

Routing

IntentRoute
Plan a study, screener, or interview guideRoute A: Plan
Build or refine a personaRoute B: Persona
Run synthetic interviews against personasRoute C: Simulate
Have transcripts (synthetic or real), need a reportRoute D: Synthesize

If the user's intent is ambiguous, ask one clarifying question.

Route A: Plan

Create a research plan, screening questionnaire, interview guide, and a recruitment and incentives plan. Do: Follow references/planner.md. Incentive design is mandatory (Phase 3). Use a neutral incentive, never free or early product access, for discovery.

Route B: Persona

Build a new persona or refine an existing one. Do: Follow references/persona-builder.md. Never hand the user the blank template; interview them about a real person (or extract from their raw material: transcripts, tickets, notes) and write the file for them, marking everything inferred with [ASSUMED: confirm]. personas/_TEMPLATE.md defines the structure; personas/example-mara-freelance-designer.md shows the level of specificity required (it is fictional; real personas must not be).

Route C: Simulate

Run synthetic interviews: embody one or more personas and answer an interview guide in character. Do: Follow run-synthetic-interview.md.

Route D: Synthesize

Turn transcripts into an evidence-backed report (themes, findings, opportunities). Do: Follow references/synthesis.md. Hard rule: a theme supported only by synthetic transcripts is a hypothesis, never a finding.

Where artifacts live

The skill is methodology only. Write study artifacts into the user's project, not into the skill directory. Suggested layout:

code
research/
  plan/            # Route A outputs: plan, screener, guide
  personas/        # Route B outputs: one file per persona
  synthetic-runs/  # Route C outputs: transcript + fidelity note, dated
  interviews/      # real-participant transcripts and notes (highest-grounding source)
  findings/        # Route D outputs: synthesis reports

If the user already has a research directory convention, follow theirs.

Files

code
synthetic-customer-discovery/
  SKILL.md                       # this file
  run-synthetic-interview.md     # Route C, the persona interview runner
  personas/
    _TEMPLATE.md                 # persona structure (the core of the method)
    example-mara-freelance-designer.md  # fictional worked example
  references/
    planner.md                   # Route A: plan, screener, guide, recruitment, incentives
    persona-builder.md           # Route B: guided persona creation (interview / extract / draft)
    synthesis.md                 # Route D: transcripts to evidence-backed report
  examples/
    example-synthetic-run.md     # what a Route C output looks like

Install & Usage

1
Create the skills directory
mkdir -p .claude/skills
2
Download the skill file
mkdir -p .claude/skills && curl -o .claude/skills/synthetic-customer-discovery.md https://raw.githubusercontent.com/kdykes/synthetic-customer-discovery/main/SKILL.md
3
Invoke in Claude Code
/synthetic-customer-discovery
View source on GitHub
testing

Frequently Asked Questions

What is synthetic-customer-discovery?

Customer discovery with grounded synthetic personas. Plan interview studies, build evidence-grounded persona files, run synthetic discovery interviews against them, and synthesize transcripts (real or synthetic) into evidence-backed reports. Use when planning customer or user interviews, writing screeners or interview guides, building or refining personas or an ICP profile, pressure-testing positioning or pricing hypotheses before talking to real people, or synthesizing interview transcripts. Synthetic output is always framed as hypothesis, never as validation.

How to install synthetic-customer-discovery?

To install synthetic-customer-discovery, create the .claude/skills directory in your project, then run the curl command to download the skill file. Once installed, invoke it in Claude Code with /synthetic-customer-discovery.

What is synthetic-customer-discovery best for?

synthetic-customer-discovery is a community categorized under General. It is designed for: testing. Created by kdykes.