Tangentiality

Classify spoken transcript fragments as TANG or NO-TANG based on topic drift.

Updated Nov 18, 2025

Search Tags:#research #language-disorder #clinical-speech #differential-diagnosis #tangentiality #speech-analysis

Ready to run

npx skills add https://github.com/Kikolo3000/topsy_databaseprocessing-agent --skill tangentiality

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Tangentiality
Source: https://github.com/Kikolo3000/topsy_databaseprocessing-agent/tree/main/skills/TAN
Command: npx skills add https://github.com/Kikolo3000/topsy_databaseprocessing-agent --skill tangentiality

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the classification of spoken text into Tangentiality (TANG) or No Tangentiality (NO-TANG), helping researchers and clinicians rapidly label transcripts for subsequent analysis.

Core Features & Use Cases

Topic drift detection: detects when discourse gradually drifts away from the initial topic.
Deterministic labeling: assigns TANG or NO-TANG using defined criteria and the Skill's frontmatter context.
Research workflows: supports labeling interview transcripts, clinical assessments, and therapy notes for language-thought-disorder studies.

Quick Start

Provide a text fragment to classify and receive a TANG or NO-TANG label.

Frequently Asked Questions about Tangentiality

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

FAQPage Schema

How do I detect tangentiality in clinical speech transcripts for differential diagnosis?▼

Detect tangentiality in clinical speech transcripts by analyzing topic drift in interview fragments and assigning a deterministic TANG or NO-TANG label for differential diagnosis workflows. The classification uses defined criteria to evaluate variable-length discourse.

What is tangentiality in language-disorder speech analysis?▼

Tangentiality in language-disorder speech analysis is the phenomenon where spoken discourse gradually drifts away from the initial topic. Identifying this topic drift helps researchers label transcripts for thought-disorder studies.

Can I use automated labeling for variable-length interview transcripts in research datasets?▼

You can use automated labeling for variable-length interview transcripts in research datasets. The skill processes variable-length fragments and applies deterministic rules to label clinical assessments and therapy notes.

How do I classify spoken text fragments into TANG or NO-TANG categories?▼

Classify spoken text fragments into TANG or NO-TANG categories by providing the text fragment to the skill. It uses a deterministic set of rules described in its context to evaluate topic drift and return the appropriate label.

Does the speech analysis skill require manual configuration to detect topic drift?▼

The speech analysis skill does not require manual configuration to detect topic drift. It uses a deterministic set of rules loaded from its context to automatically guide the classification of topic drift in spoken fragments.