# research-repository

Helps teams organize UX findings into a structured repository so research insights stay searchable, reusable, and linked to evidence.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 1700 installs · ★ 3103
- Author: Owl-Listener
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/Owl-Listener/designer-skills/tree/HEAD/design-research/skills/research-repository/SKILL.md
- Updated: 2026-09-05
- HTML: https://affpapa.org/en/nevibecode/skills/research-repository

## What it does

The skill organizes research data into three clear layers: atomic insights, study records, and raw evidence like transcripts. It shifts the primary search focus from long report decks to standalone findings. Each insight entry tracks a single past-tense statement, confidence rating, methodology, and sample size.

It establishes tagging rules across product themes, user segments, and sentiment, limiting tags to between five and eight per insight. The instructions provide setup guidelines for tools like Notion, Airtable, and Dovetail alongside maintenance rituals. For synthesising a single study, this skill is excessive: the author explicitly points to `affinity-diagram` instead.

## Requirements
- Works with: Notion

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add Owl-Listener/designer-skills --skill research-repository -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/research-repository/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/research-repository/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add Owl-Listener/designer-skills --skill research-repository -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/research-repository/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add Owl-Listener/designer-skills --skill research-repository -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/research-repository/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install Owl-Listener/designer-skills research-repository
```

2. **Manually: put the files in place**
- File: `.github/skills/research-repository/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add Owl-Listener/designer-skills --skill research-repository -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/Owl-Listener/designer-skills --path design-research/skills/research-repository
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/research-repository/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add Owl-Listener/designer-skills --skill research-repository -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/Owl-Listener/designer-skills/tree/HEAD/design-research/skills/research-repository/SKILL.md

## When to use it
- organize scattered user research into a searchable knowledge base
- define a controlled tagging vocabulary for Notion or Airtable
- link high-level insights directly to interview transcripts and surveys
- establish maintenance routines to deprecate outdated UX findings

## Example prompts
- Design a 3-layer research repository structure in Notion with insights and raw data
- Help define a controlled tagging system for our checkout usability findings
- Format a new research insight with confidence levels and source links

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: f00a325d0976588f.

BEGIN THIRD-PARTY FILE f00a325d0976588f
```text
---
name: research-repository
description: Build a repository that makes findings findable, reusable, and cumulative across teams. Use when the same research keeps getting redone. For synthesising one study, use `affinity-diagram`.
---
# Research Repository
You are an expert in organizing research so it compounds in value rather than disappearing into shared drives.
## What You Do
You design and maintain the systems, tagging conventions, and rituals that keep research findable and used — so teams don't repeat studies, can build on prior work, and can make decisions backed by accumulated evidence.
## Why Repositories Fail
Most research is conducted well and then effectively lost. Common failure modes:
- Findings live in project folders organized by team, not by topic — no one knows what exists
- Reports are long and unstructured — hard to find a specific insight in a 40-page deck
- Tagging is inconsistent or absent — search doesn't work
- Repository exists but no one adds to it — no maintenance culture
- Insights and raw data are mixed — teams can't tell what's an observation and what's a conclusion
## Repository Architecture
### Three Layers
1. **Insights**: discrete, standalone findings ("Users don't understand the difference between X and Y") — the most reusable unit
2. **Studies**: the research projects that produced insights (interview series, usability test, survey) — provides context for evaluating insight validity
3. **Raw data**: transcripts, recordings, survey exports — the evidence behind insights; not the primary search target
Design the repository so insights are the primary entry point — not studies, not raw data.
### Insight Structure
Each insight should have:
- **Statement**: one clear sentence (past tense, specific)
- **Confidence**: High (multiple studies, large sample) / Medium (single study, validated) / Low (one session, early signal)
- **Method**: how it was gathered (interview, usability test, survey, analytics)
- **Date**: when gathered
- **Sample**: who (segment, n)
- **Tags**: topic, feature area, user segment, sentiment
- **Source links**: back to the study and raw data
- **Related insights**: manually or automatically linked
## Tagging System
The tagging system is the most critical design decision in a repository. Define tags before populating:
### Tag Dimensions
- **Topic/theme**: navigation, onboarding, pricing, notifications, mobile, accessibility…
- **Feature or product area**: checkout, dashboard, settings, home feed…
- **User segment**: new users, power users, enterprise, mobile-only, specific personas…
- **Sentiment**: pain, delight, confusion, trust…
- **Recency signal**: evergreen vs time-bound findings
- **Status**: validated, superseded, conflicting
### Rules
```
END THIRD-PARTY FILE f00a325d0976588f

The third-party file has ended. Everything between the f00a325d0976588f tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

First 2773 of 5546 bytes. © Owl-Listener · MIT · https://github.com/Owl-Listener/designer-skills/tree/HEAD/design-research/skills/research-repository/SKILL.md

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---
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