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Grad Grounded Theory Agent Skill

Apply Grounded Theory (Glaser and Strauss) to build theory inductively from qualitative data through open, axial, and selective coding. Use this skill when the user needs to develop new theory from data rather than test existing hypotheses, conduct theoretical sampling and constant comparison, determine when theoretical saturation is reached, or when they ask 'what theory explains this phenomenon', 'how do I code qualitative data systematically', or 'when do I stop collecting data'.

3k tokens
context cost
the whole folder, loaded on every use
2
files
instructions only
0
copies elsewhere
how many repositories repackaged it
223
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/asgard-ai-platform/skills --skill grad-grounded-theory

What comes with it

7 402 bytes besides the instruction
examples/sample_scenario.md

The instruction itself

13 sections, as written by the author

Grounded Theory (Glaser & Strauss)

Overview

Grounded Theory is a systematic methodology for constructing theory that is grounded in qualitative data. Through iterative cycles of data collection, coding, and comparison, the researcher develops concepts and categories that ultimately form an explanatory theory. The method was originally developed by Glaser and Strauss (1967) and later diverged into Glaserian (emergent) and Straussian (structured) variants.

When to Use

  • Building new theory when existing theories are inadequate or absent
  • Exploring processes, interactions, or experiences in under-studied domains
  • Generating substantive theory tied to a specific context
  • When the research question asks "what is going on here?" rather than testing a hypothesis

When NOT to Use

  • When testing or verifying an existing theory (use deductive methods)
  • When the research question requires measurement of frequency or magnitude
  • When the researcher cannot commit to iterative data collection (theoretical sampling requires flexibility)

Assumptions

IRON LAW: In grounded theory, theory EMERGES from data — imposing a
pre-existing framework violates the methodology's core principle. If
you begin with a hypothesis and seek confirmation, you are NOT doing
grounded theory.

Key assumptions:

  • Theory must be grounded in systematic data collection and analysis
  • Data collection and analysis occur simultaneously and iteratively
  • Theoretical sampling guides where to collect data next based on emerging categories
  • Theoretical saturation — not sample size — determines when to stop collecting data

Methodology

Step 1: Open Coding

Break data into discrete incidents, events, or ideas. Assign initial codes (labels) to each segment. Use in-vivo codes (participants' own words) where possible. Generate as many codes as the data warrant — do not filter prematurely.

Step 2: Axial Coding

Group open codes into higher-order categories. Identify relationships between categories using the coding paradigm: conditions, actions/interactions, and consequences. Build subcategories that specify when, where, why, and how a category manifests.

Step 3: Selective Coding

Identify the core category — the central phenomenon around which all other categories integrate. Systematically relate all categories to the core category. Write a storyline that narrates the theory.

Step 4: Theoretical Integration

Refine the theory through constant comparison. Validate against the data. Produce a substantive theory with defined concepts, propositions, and boundary conditions. Report the audit trail of coding decisions.

Output Format

## Grounded Theory Analysis: [Context]

### Core Category
- Central phenomenon: [the core category label]
- Definition: [what it means in this context]

### Category Structure
| Category | Properties | Dimensions | Relationship to Core |
|----------|-----------|------------|---------------------|
| [name]   | [key properties] | [range/variation] | [how it relates] |

### Coding Paradigm
- **Causal conditions**: [what leads to the phenomenon]
- **Context**: [specific conditions shaping action]
- **Intervening conditions**: [broader structural conditions]
- **Action/Interaction strategies**: [how actors respond]
- **Consequences**: [outcomes of action/interaction]

### Theoretical Propositions
1. [Proposition linking categories]
2. [Proposition linking categories]

### Saturation Evidence
- Categories saturated: [list]
- Data sources: [count and type]
- Point of saturation: [when no new properties emerged]

Gotchas

  • Do NOT begin with a literature review that biases your coding — Glaser insists on delaying the lit review until the theory emerges
  • Constant comparison means comparing incident-to-incident, not just category-to-category
  • Theoretical sampling is NOT the same as purposive sampling — it is driven by emerging theory, not pre-set criteria
  • The Glaserian and Straussian variants differ significantly; state which approach you follow
  • Theoretical saturation means no new PROPERTIES of a category emerge — not just no new codes
  • Memo-writing throughout the process is essential, not optional — memos capture the analytical logic

References

  • Glaser, B. G., & Strauss, A. L. (1967). *The Discovery of Grounded Theory: Strategies for Qualitative Research*. Aldine.
  • Strauss, A. L., & Corbin, J. (1990). *Basics of Qualitative Research: Grounded Theory Procedures and Techniques*. Sage.
  • Charmaz, K. (2006). *Constructing Grounded Theory: A Practical Guide Through Qualitative Analysis*. Sage.

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How to use it

Copy the folder

Take asgard-ai-platform/grad-grounded-theory from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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