affinity-diagram
Cluster many qualitative data points into themes and insight statements. Use when synthesising across multiple sessions or sources. For a single transcript use summarize-interview; for one segment's inner state use empathy-map.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/owl-listener/designer-skills --skill affinity-diagram- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads affinity-diagram automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Affinity Diagram
Organize qualitative research data into themed clusters and insight statements.
Context
You are a UX researcher synthesizing qualitative data for $ARGUMENTS. If the user provides files (interview notes, observation data, survey responses), read them first.
Instructions
- Extract data points: Pull individual observations, quotes, and notes from the raw data.
- Bottom-up clustering: Group related data points into natural clusters (do not start with predefined categories).
- Name each cluster: Create descriptive theme labels that capture the essence of each group.
- Create hierarchy: Organize clusters into higher-level themes (typically 3-5 top-level themes).
- Write insight statements: For each theme, write a clear insight statement that captures the "so what?"
- Identify patterns: Note frequency, intensity, and connections between themes.
- Prioritize: Rank insights by impact on design decisions.
- Present the affinity diagram as a structured hierarchy with insight statements and supporting evidence.
Cross-Interview Sampling Principle
Index evenly across all participants. When working from multiple interview transcripts, process each one fully before clustering. Do not over-represent early transcripts or the most recent input.
- Treat each participant as an equal source of signal
- Tag every observation with its participant ID (P1, P2, P3...) before grouping
- After clustering, check that each participant appears at least once in the output — if any are absent, go back
- Patterns that appear in only one interview should be flagged as single-source, not discarded
This prevents the common LLM failure mode of building themes from the first one or two transcripts and fitting the rest retroactively.
FAQ
What does the affinity-diagram skill do?
Cluster many qualitative data points into themes and insight statements. Use when synthesising across multiple sessions or sources. For a single transcript use summarize-interview; for one segment's inner state use empathy-map.
How do I install affinity-diagram?
Run npx skills add https://github.com/owl-listener/designer-skills --skill affinity-diagram in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/affinity-diagram/ (personal) or .claude/skills/affinity-diagram/ (project).
Which AI agents can use affinity-diagram?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is affinity-diagram safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains affinity-diagram?
It is published by owl-listener in owl-listener/designer-skills. It has 2,092 recorded installs.
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