grounded-coding

Generate grounded theory coding from interview transcripts with open, axial, and selective coding.

265|23|Updated Feb 7, 2026
One-click install
npx skills add https://github.com/yipng05-max/-skills --skill grounded-coding-yipng05-max
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: grounded-coding
Source: https://github.com/yipng05-max/-skills/tree/main/grounded-coding
Command: npx skills add https://github.com/yipng05-max/-skills --skill grounded-coding-yipng05-max

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill helps you systematically code interview transcripts or other qualitative data using grounded theory, producing structured open coding, axial (paradigm model) coding, and optional selective coding outputs with exportable summaries.

Core Features & Use Cases

  • Programmatic grounded theory coding: Performs open coding (event → category → analytic category), axial coding (properties/dimensions, paradigm model relations), and guides selective coding (core category → research question → storyline).
  • Multi-interview accumulation: Supports constant comparison across multiple interviews, including reuse and revision of an existing coding table.
  • Structured outputs and exports: Saves per-interview results into Markdown files and can generate an aggregated Excel once multiple interviews are completed.

Quick Start

Upload or provide the local path to your interview text file, then ask for grounded coding so the Skill can start by collecting the missing study context (research field, topic, interviewee info, and interview order/previous coding table if applicable).

Frequently Asked Questions about grounded-coding

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

FAQPage Schema
How do I perform grounded theory coding on interview transcripts?

Grounded theory coding on interview transcripts is processed through open coding, axial paradigm model analysis, and optional selective coding. The skill requires you to upload or provide a local file path to your qualitative text to generate structured coding outputs.

What is the best way to apply axial coding and constant comparison across multiple interviews?

Applying axial coding and constant comparison across multiple interviews involves reusing and revising an existing coding table to build categories. This multi-interview accumulation ensures paradigm model relations are systematically refined across all qualitative data.

Can I export qualitative coding results to Markdown and Excel?

You can export qualitative coding results to Markdown and aggregated Excel formats using available scripts. Per-interview results are saved into Markdown files, and once multiple interviews are coded, an aggregated Excel spreadsheet can be generated.

Do I need to provide study context before starting open coding analysis?

You need to provide study context before starting open coding analysis, including the research field, topic, interviewee information, and interview order. Providing a previous coding table if applicable supports accurate constant comparison and category building.

How does selective coding integrate a core category into a storyline?

Selective coding integrates a core category into a storyline by connecting axial paradigm model relations to the research question. This guides the generation of propositions and a cohesive narrative structure for final theory integration.