skills.rest
disabledbydesign
disabledbydesignCOMMUNITY
Explore all skills by this author →
GitHub

discourse-analysis

Analyze texts to produce structured discourse profiles using spaCy.

Updated Apr 14, 2026
Search Tags:#frameworks#nlp#linguistics#transitivity#discourse-analysis#cda#stance-engagement
One-click install
npx skills add https://github.com/disabledbydesign/cyborg-methodologies --skill discourse-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: discourse-analysis
Source: https://github.com/disabledbydesign/cyborg-methodologies/tree/main/discourse-analysis
Command: npx skills add https://github.com/disabledbydesign/cyborg-methodologies --skill discourse-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a framework-informed workflow to convert diverse texts into structured discourse profiles, capturing ideational, interpersonal, and textual metafunctions to support transparent interpretation and comparison.

Core Features & Use Cases

  • Structured discourse profiling: Extracts transitivity, modality, stance, engagement, and theme patterns to illuminate how texts construct meaning.
  • Cross-text comparison: Enables researchers to compare patterns across academic, policy, media, and ethnographic materials to surface similarities and differences.
  • Contextual integration: Generates outputs suitable for inclusion in research notes and project-context documentation, enabling traceable analytical decisions.

Quick Start

Provide a sample text and receive a structured discourse profile plus a concise analytic summary.

Frequently Asked Questions about discourse-analysis

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

FAQPage Schema
How do I extract transitivity and modality patterns from text for discourse analysis?▼

Discourse analysis extracts transitivity and modality patterns by tokenizing and parsing text with spaCy to produce a structured profile. This reveals how texts construct ideational and interpersonal meaning across academic, policy, and media materials.

What is the best way to compare stance and engagement across multiple policy documents?▼

Comparing stance and engagement across policy documents requires a structured discourse profile for each text. Cross-text comparison surfaces similarities and differences in how voices are constructed and presuppositions are framed.

Can I use NLP libraries like spaCy to analyze ethnographic materials for linguistic features?▼

You can analyze ethnographic materials using spaCy and optional NLP libraries to tokenize and parse text. The pipeline extracts lexical and syntactic features to generate a structured discourse profile suitable for research notes.

How do I surface hidden presuppositions in media texts using critical discourse analysis?▼

Surfacing presuppositions in media texts involves applying critical discourse analysis frameworks to extract stance, engagement, and theme patterns. This structured profiling illuminates how texts construct meaning and position voices.

Does discourse profiling work for comparing academic and media materials?▼

Discourse profiling works across academic, policy, media, and ethnographic materials to compare texts. It captures ideational, interpersonal, and textual metafunctions to support transparent interpretation and cross-text comparison.

Related Skills

Explore More Education & Research Skills→
ShinyGuaShinyGua

ar-retrieval

Generate deduplicated SourceRecord entries and a corpus_manifest from workspace inputs.

Community
Advanced
kerolos-saaidkerolos-saaid

speckit-clarify

Identify underspecified areas in feature specs and generate up to five clarifying questions.

Community
Advanced
xjtulycxjtulyc
33

spacy-nlp-pipeline

Build spaCy pipelines to extract tokens, entities, and dependencies from text.

Community
Intermediate
blackpwnguinblackpwnguin
1

story-explanation

Generates structured narrative explanations from content using UltraThink-driven framing analysis.

Community
Advanced