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discover-interview-synthesis

Synthesizes user research interviews into actionable insights, patterns, and recommendations. Use after conducting user interviews, customer calls, or usability sessions to extract and communicate findings across participants. Distinct from foundation-meeting-recap, which summarizes one internal meeting for its attendees; this skill aggregates research conversations into evidence-backed findings.

科研715skills/discover-interview-synthesis/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/product-on-purpose/pm-skills/discover-interview-synthesis/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Interview Synthesis

An interview synthesis transforms raw user research data into structured insights that drive product decisions. Rather than simply listing what participants said, a good synthesis identifies patterns across conversations, connects observations to underlying user needs, and translates findings into actionable recommendations.

When to Use

  • After completing a round of user interviews (typically 5+ participants)
  • Following customer discovery calls or sales feedback sessions
  • After usability testing sessions to consolidate observations
  • When stakeholders need a summary of research findings
  • Before ideation sessions to ground the team in user reality

When NOT to Use

  • You are summarizing one internal meeting for its attendees -> use foundation-meeting-recap
  • You need patterns across multiple meetings over time -> use foundation-meeting-synthesize
  • Your data is survey responses rather than interviews -> use measure-survey-analysis
  • The findings are synthesized and you are ready to frame the problem -> use define-problem-statement
  • You have synthesized findings and want to map them onto a customer's journey across stages and touchpoints -> use discover-journey-map

Instructions

When asked to synthesize interview findings, follow these steps:

  1. Gather the Raw Material Collect all interview notes, transcripts, or recordings. Ensure you have data from at least 3 participants to identify meaningful patterns. Note the research objective and methodology used.

  2. Create Participant Profiles Document each participant with relevant context: their role, segment, tenure, and any notable characteristics. This helps readers assess the representativeness of findings.

  3. Identify Recurring Themes Read through all notes and tag observations by topic. Look for themes that appear across multiple participants (ideally 3+). Distinguish between frequently mentioned topics and one-off comments.

  4. Extract Meaningful Quotes Capture 3-5 verbatim quotes per theme that powerfully illustrate the insight. Good quotes are specific, emotional, or particularly articulate. Always attribute quotes to participant IDs.

  5. Synthesize into Insights Transform themes into insight statements. An insight goes beyond observation ("users mentioned X") to interpretation ("users need Y because of Z"). Connect what you heard to why it matters.

  6. Formulate Recommendations Based on the insights, propose prioritized actions. Each recommendation should tie directly to an insight. Note confidence level based on strength of evidence.

  7. Document Limitations Acknowledge what you didn't learn, sample biases, or areas needing further research. Honest limitations increase credibility.

Project Memory Contract

Active only when .claude/pm-skills.local.md exists. With no file, ignore this section entirely and behave exactly as described above.

  • Reads: phase and active_initiative, so findings are framed against the initiative in flight instead of asking you to restate it.
  • Writes: the personas and findings as an interpretation artifact, so a later skill can consume them without you pasting them again.
  • Posture: propose the entry and wait for confirmation before writing, unless memory_auto_append: true is set, in which case append and echo what was written.
  • Write discipline: re-read the file immediately before writing, never from the copy that produced the proposal. If it changed in between, merge your entry into the current state and re-propose rather than overwriting; add only your own entry and leave every other field and section byte-identical. Nothing enforces this at runtime and the file is gitignored, so a careless whole-file write loses another session's work with no way to recover it.

This is the writer half of the loop the cohort exists to demonstrate: what this skill records, deliver-prd later reads.

Output Format

Use the template in references/TEMPLATE.md to structure the output. A complete synthesis fills every template section: Research Overview; Key Themes; Notable Quotes; Insights; Recommendations; and Appendix.

Quality Checklist

Before finalizing, verify:

  • Themes are supported by evidence from 3+ participants
  • Quotes are verbatim and attributed to participant IDs
  • Insights explain "why" not just "what"
  • Recommendations are specific and actionable
  • Participant identities are protected (no PII)
  • Limitations and biases are acknowledged

Examples

See references/EXAMPLE.md for a completed example.

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