expert-interviewer

Extract domain knowledge from experts via structured interviews into reviewed artifacts.

8|1|Updated Jan 24, 2026
One-click install
npx skills add https://github.com/bordenet/superpowers-plus --skill expert-interviewer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: expert-interviewer
Source: https://github.com/bordenet/superpowers-plus/tree/main/skills/research/expert-interviewer
Command: npx skills add https://github.com/bordenet/superpowers-plus --skill expert-interviewer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Extracts and preserves institutional and domain expertise that is otherwise lost to shallow notes or unfocused conversations, producing a coherent, audience‑appropriate artifact ready for review and publication.

Core Features & Use Cases

  • Phase-driven interviewing: Enforces frame-setting, research integration, one-question-per-message interviewing, synthesis checkpoints, saturation detection, and a hard stop to avoid premature drafting.
  • Evidence-first drafting and review: Generates a traceable first draft tied to interview answers and research, runs an automated content-review sub-agent, and requires structured user approval before publishing.
  • Use Cases: Capture subject-matter knowledge for wikis, create reference docs during employee transitions, and produce problem-space overviews for product or engineering teams.

Quick Start

Conduct a structured expert interview to capture the payments domain for a wiki page by following the phase checklist, synthesizing after each answer, and producing a draft for automated review and user approval.

Frequently Asked Questions about expert-interviewer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I capture expert knowledge for a wiki page before an employee transitions?▼

To capture expert knowledge for a wiki page, conduct structured interviews to extract domain knowledge and synthesize answers into a reviewed, publishable artifact. This preserves institutional expertise through a phased workflow with frame-setting, research integration, and synthesis checkpoints.

What is the best way to document domain expertise for onboarding material?▼

The best way to document domain expertise for onboarding material is using a phased interview workflow that extracts knowledge through one-question-per-message sessions. It enforces saturation detection to prevent premature drafting, ensuring comprehensive reference docs.

How does the structured interview process work for knowledge capture?▼

The structured interview process for knowledge capture works by enforcing a phased workflow: frame-setting, research integration, one-question-per-message interviewing, synthesis checkpoints, and saturation detection. This ensures a coherent, audience-appropriate artifact.

Can I automate the review pipeline when creating reference docs from interviews?▼

Yes, you can automate the review pipeline when creating reference docs from interviews. The process generates a traceable first draft tied to interview answers and research, runs an automated content-review sub-agent, and requires structured user approval before publishing.

Does this approach prevent premature drafting when extracting subject-matter knowledge?▼

Yes, this approach prevents premature drafting when extracting subject-matter knowledge by enforcing a hard stop after the interview phases. It uses saturation detection and synthesis checkpoints to ensure all necessary domain expertise is collected before drafting begins.

What kind of artifacts can I produce from expert interviews?▼

From expert interviews, you can produce publishable artifacts such as wiki pages, reference documents, problem-space overviews, and onboarding material. These artifacts are generated as traceable first drafts tied to interview answers and research.