Agent Skillsanthropics/knowledge-work-plugins › research-synthesis

research-synthesis

GitHub

将用户研究数据(如访谈、问卷、可用性测试)综合为主题、洞察和建议。适用于从原始反馈中提炼模式、划分用户群并确定优先行动步骤的场景。

design/skills/research-synthesis/SKILL.md anthropics/knowledge-work-plugins

Trigger Scenarios

需要分析用户访谈记录或笔记 需从调查结果中提取关键主题

Install

npx skills add anthropics/knowledge-work-plugins --skill research-synthesis -g -y
More Options

Non-standard path

npx skills add https://github.com/anthropics/knowledge-work-plugins/tree/main/design/skills/research-synthesis -g -y

Use without installing

npx skills use anthropics/knowledge-work-plugins@research-synthesis

指定 Agent (Claude Code)

npx skills add anthropics/knowledge-work-plugins --skill research-synthesis -a claude-code -g -y

安装 repo 全部 skill

npx skills add anthropics/knowledge-work-plugins --all -g -y

预览 repo 内 skill

npx skills add anthropics/knowledge-work-plugins --list

SKILL.md

Frontmatter
{
    "name": "research-synthesis",
    "description": "Synthesize user research into themes, insights, and recommendations. Use when you have interview transcripts, survey results, usability test notes, support tickets, or NPS responses that need to be distilled into patterns, user segments, and prioritized next steps.",
    "argument-hint": "<research data, transcripts, or survey results>"
}

/research-synthesis

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Synthesize user research data into actionable insights. See the user-research skill for research methods, interview guides, and analysis frameworks.

Usage

/research-synthesis $ARGUMENTS

What I Accept

  • Interview transcripts or notes
  • Survey results (CSV, pasted data)
  • Usability test recordings or notes
  • Support tickets or feedback
  • NPS/CSAT responses
  • App store reviews

Output

## Research Synthesis: [Study Name]
**Method:** [Interviews / Survey / Usability Test] | **Participants:** [X]
**Date:** [Date range] | **Researcher:** [Name]

### Executive Summary
[3-4 sentence overview of key findings]

### Key Themes

#### Theme 1: [Name]
**Prevalence:** [X of Y participants]
**Summary:** [What this theme is about]
**Supporting Evidence:**
- "[Quote]" — P[X]
- "[Quote]" — P[X]
**Implication:** [What this means for the product]

#### Theme 2: [Name]
[Same format]

### Insights → Opportunities

| Insight | Opportunity | Impact | Effort |
|---------|-------------|--------|--------|
| [What we learned] | [What we could do] | High/Med/Low | High/Med/Low |

### User Segments Identified
| Segment | Characteristics | Needs | Size |
|---------|----------------|-------|------|
| [Name] | [Description] | [Key needs] | [Rough %] |

### Recommendations
1. **[High priority]** — [Why, based on which findings]
2. **[Medium priority]** — [Why]
3. **[Lower priority]** — [Why]

### Questions for Further Research
- [What we still don't know]

### Methodology Notes
[How the research was conducted, any limitations or biases to note]

If Connectors Available

If ~~user feedback is connected:

  • Pull support tickets, feature requests, and NPS responses to supplement research data
  • Cross-reference themes with real user complaints and requests

If ~~product analytics is connected:

  • Validate qualitative findings with usage data and behavioral metrics
  • Quantify the impact of identified pain points

If ~~knowledge base is connected:

  • Search for prior research studies and findings to compare against
  • Publish the synthesis to your research repository

Tips

  1. Include raw quotes — Direct participant quotes make insights credible and memorable.
  2. Separate observations from interpretations — "5 of 8 users clicked the wrong button" is an observation. "The button placement is confusing" is an interpretation.
  3. Quantify where possible — "Most users" is vague. "7 of 10 users" is specific.

Version History

  • 6f13415 Current 2026-07-05 18:28

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Metadata

Files
0
Version
69f24af
Hash
40048615
Indexed
2026-07-05 18:28

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