Skip to content
cccskills
FreePublished on GitHub

affinity-diagram

Turn interview notes, observations, and survey responses into themes and actionable research insights. Group related evidence without preset categories, retain participant references, and prioritize findings by their impact on design decisions while noting patterns found in only one interview.

OriginalShow the original description

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`.

Run score Not tested

See how to install

Good for

  • Synthesize findings across multiple interviews
  • Organize observation notes and survey responses
  • Prioritize research insights for design decisions
  • Track participant evidence behind each theme

Files included (1)

  • SKILL.md2.0 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

  1. Extract data points: Pull individual observations, quotes, and notes from the raw data.
  2. Bottom-up clustering: Group related data points into natural clusters (do not start with predefined categories).
  3. Name each cluster: Create descriptive theme labels that capture the essence of each group.
  4. Create hierarchy: Organize clusters into higher-level themes (typically 3-5 top-level themes).
  5. Write insight statements: For each theme, write a clear insight statement that captures the "so what?"
  6. Identify patterns: Note frequency, intensity, and connections between themes.
  7. Prioritize: Rank insights by impact on design decisions.
  8. 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.

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

a-b-test-design

FreeSummary

Plan A/B experiments to measure the effect of a design change. Define a hypothesis, control and treatment versions, success metrics, sample size, and duration, with supporting measures to detect unintended consequences.

  • Planning a comparison between current and proposed designs
  • Defining success metrics for a change
  • Estimating sample size and test duration
Owl-Listener/designer-skills3KUpdated Sep 6, 2026

Assess an existing interface against WCAG 2.2 accessibility guidelines. Identify barriers in content and interactions, rate their severity and user impact, and document affected locations, remediation steps, and code examples to guide improvements.

  • Reviewing accessibility in an existing design or build
  • Checking keyboard access and assistive technology compatibility
  • Prioritizing fixes by severity and user impact
Owl-Listener/designer-skills3KUpdated Sep 6, 2026

Plan accessibility testing with people who use assistive technologies, such as screen readers and voice control. Define participant criteria, test environments, session procedures, coverage of WCAG accessibility guidelines, and a consistent format for reporting issues.

  • Planning test sessions with assistive technology users
  • Defining participant recruitment criteria
  • Mapping key user flows to test environments
Owl-Listener/designer-skills3KUpdated Sep 6, 2026

Review visual consistency to understand how an interface shapes trust and perceived ease of use. Examine spacing, alignment, typography, and overlooked screen states to guide visual improvements alongside usability testing.

  • Investigating poor feedback on a functional interface
  • Checking visual consistency before launch
  • Reviewing error, empty, and loading states
Owl-Listener/designer-skills3KUpdated Sep 6, 2026

Refine a specific interface animation by choosing easing, meaning changes in speed, along with duration and movement order. Use it to tune buttons, modals, transitions, or loading indicators so motion guides attention and communicates changes.

  • Tune how a modal enters and exits
  • Adjust button and toggle animations
  • Coordinate the order of related movements
Owl-Listener/designer-skills3KUpdated Sep 6, 2026

Read conversion steps, retention curves, and recorded user actions to investigate why people leave a product. Check tracking issues first, then produce ranked design hypotheses with clear evidence that would support or rule out each explanation.

  • Investigating where users abandon a signup flow
  • Interpreting changes in user retention
  • Checking tracking issues before changing a design
Owl-Listener/designer-skills3KUpdated Sep 6, 2026

See all skills by Owl-Listener

Report a problem with this skill