---
id: daily-research-synthesis
name: "research-synthesis"
url: https://skills.yangsir.net/skill/daily-research-synthesis
author: anthropics
domain: data-ai
tags: ["research", "ux", "product-management", "data-analysis", "interviews"]
install_count: 4000
rating: 4.40 (20 reviews)
github: https://github.com/anthropics/knowledge-work-plugins
---

# research-synthesis

> 面向用户体验研究员和产品经理的研究综合工具。将访谈记录、问卷结果、可用性测试笔记等多源研究数据转化为结构化洞察。自动提取主题、识别用户细分、生成洞察-机会矩阵，并提供基于证据的产品改进建议。适用于敏捷研究周期，支持多格式数据输入。

**Stats**: 4,000 installs · 4.4/5 (20 reviews)

## Before / After 对比

### 研究报告自动化生成

**Before**:

在没有 `research-synthesis` 技能时，研究人员需要手动处理大量的原始研究数据，包括访谈记录、调查结果和用户反馈。这涉及耗时的人工阅读、标记和归纳，以识别关键主题和模式。研究人员必须逐一提取支持性引证，并手动计算主题的普遍性。随后，还需要自行设计并填充洞察-机会矩阵、用户细分表和建议列表。整个报告的结构、格式和一致性都依赖于人工操作，耗费大量精力，且容易因数据量大而遗漏关键信息或引入主观偏差，导致报告生成周期长、效率低下。

**After**:

使用 `research-synthesis` 技能后，研究人员只需将原始数据（如访谈记录、调查结果、用户反馈）作为输入提供。该技能将自动进行数据综合分析，智能提取关键主题、计算其普遍性，并提供支持性引证。它能快速生成一个结构化的研究报告，包含执行摘要、关键主题、洞察-机会矩阵、用户细分、建议和待研究问题等预定义部分。如果连接了其他工具（如用户反馈、产品分析），还能自动整合更多数据源，验证定性发现。这极大地减少了手动工作量，加速了报告生成过程，确保了报告的全面性、一致性和专业性，使研究人员能专注于更高价值的战略思考。

| Metric | Before | After | Change |
|---|---|---|---|
| 报告生成时间 | 32小时 | 1.5小时 | -95.3% |
| 报告结构化所需工时 | 16小时 | 0.5小时 | -96.8% |
| 整合数据源数量 | 3个 | 6个 | +100% |

## Readme

# research-synthesis

# /research-synthesis

If you see unfamiliar placeholders or need to check which tools are connected, see [CONNECTORS.md](https://github.com/anthropics/knowledge-work-plugins/blob/HEAD/design/skills/research-synthesis/../../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

- **Include raw quotes** — Direct participant quotes make insights credible and memorable.

- **Separate observations from interpretations** — "5 of 8 users clicked the wrong button" is an observation. "The button placement is confusing" is an interpretation.

- **Quantify where possible** — "Most users" is vague. "7 of 10 users" is specific.

Weekly Installs266Repository[anthropics/know…-plugins](https://github.com/anthropics/knowledge-work-plugins)GitHub Stars10.3KFirst Seen12 days agoSecurity Audits[Gen Agent Trust HubPass](/anthropics/knowledge-work-plugins/research-synthesis/security/agent-trust-hub)[SocketPass](/anthropics/knowledge-work-plugins/research-synthesis/security/socket)[SnykPass](/anthropics/knowledge-work-plugins/research-synthesis/security/snyk)Installed oncodex257gemini-cli256opencode255cursor255kimi-cli254github-copilot254

---
*Source: https://skills.yangsir.net/skill/daily-research-synthesis*
*Markdown mirror: https://skills.yangsir.net/api/skill/daily-research-synthesis/markdown*