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thematic-analysis

Cluster interview codes into candidate themes using Braun and Clarke reflexive thematic analysis.

Updated Apr 17, 2026

Search Tags:#thematic analysis #qualitative research #research synthesis #theme clustering #interview coding #Braun & Clarke

Ready to run

npx skills add https://github.com/RenJW418/RenJW-Research_skill --skill thematic-analysis-renjw418

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: thematic-analysis
Source: https://github.com/RenJW418/RenJW-Research_skill/tree/main/thematic-analysis
Command: npx skills add https://github.com/RenJW418/RenJW-Research_skill --skill thematic-analysis-renjw418

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps qualitative researchers perform Braun & Clarke reflexive thematic analysis by transforming raw interview text or an existing initial coding pool into structured candidate themes, including guidance on boundary-unclear coding and naming suggestions.

Core Features & Use Cases

Two input modes: analyze from raw interview transcripts or start directly from already-made initial codes.
Braun & Clarke workflow support: performs initial coding, cross-interview pooling, candidate theme clustering, theme review, and naming suggestions (with explicit “researcher decides” handoffs).
Researcher-first guardrails: enforces reflexive principles like researcher-owned decisions for what matters, and captures ambiguous codes without forcing premature conclusions.

Quick Start

Provide your interview transcript(s) and ask the skill to run Braun & Clarke thematic analysis to produce a candidate theme table and naming options.

Frequently Asked Questions about thematic-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I turn interview transcripts into candidate themes using Braun and Clarke thematic analysis?▼

To turn interview transcripts into candidate themes, this skill applies Braun and Clarke reflexive thematic analysis by performing initial coding, cross-interview pooling, and theme clustering to output structured candidate themes.

What is the best way to cluster initial codes into themes for qualitative research?▼

Clustering initial codes into themes for qualitative research requires defensible code-to-theme grouping across interviews, reviewing theme boundaries for coherence, and tracking ambiguous codes without forcing premature conclusions.

Can I start qualitative thematic analysis directly from an existing coding pool instead of raw transcripts?▼

You can start thematic analysis directly from an existing coding pool, skipping raw transcript processing to immediately cross-interview pool codes and generate structured candidate themes tied to your research question.

Does reflexive thematic analysis let the AI decide final theme names automatically?▼

Reflexive thematic analysis enforces researcher-first guardrails, meaning the AI provides theme naming suggestions and explicit handoffs while the researcher owns all final decisions regarding what matters thematically.

How do I handle ambiguous codes when clustering themes across multiple interviews?▼

When clustering themes across multiple interviews, ambiguous codes are tracked and captured without forcing premature conclusions, allowing the researcher to review boundary-unclear coding and determine final theme inclusion.

What intermediate outputs are generated during thematic analysis of interview text?▼

Thematic analysis of interview text mandates saving intermediate outputs like initial coding pools and cross-interview code groupings, alongside final structured candidate theme tables and naming option suggestions.