Neologisms

Classify speech fragments as Neologisms or No Neologisms in clinical transcripts.

Updated Nov 18, 2025
One-click install
npx skills add https://github.com/Kikolo3000/topsy_databaseprocessing-agent --skill neologisms
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Neologisms
Source: https://github.com/Kikolo3000/topsy_databaseprocessing-agent/tree/main/skills/NEO
Command: npx skills add https://github.com/Kikolo3000/topsy_databaseprocessing-agent --skill neologisms

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps researchers and clinicians automatically classify speech fragments as Neologisms (NEO) or No Neologisms (NO-NEO), enabling consistent analysis of language thought disorders.

Core Features & Use Cases

  • Automated Neologism Detection: Identify invented words and assess whether they impair comprehension.
  • Contrastive Evaluation: Distinguish genuine neologisms from slang, borrowings, or jargon.
  • Use Case: Apply to clinical transcripts to label segments with NEO/NO-NEO and generate structured annotations for research datasets.

Quick Start

Provide a text fragment to the skill and request a NEO/NO-NEO classification along with a succinct justification.

Frequently Asked Questions about Neologisms

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

FAQPage Schema
How do I identify neologisms in clinical speech transcripts?

To identify neologisms in clinical speech transcripts, provide short text fragments to this classifier. It evaluates utterances for invented words and comprehensibility, returning a NEO or NO-NEO label with a structured rationale.

What is the difference between a neologism and slang in speech analysis?

In speech analysis, a neologism is an invented word that impairs comprehension, whereas slang does not. This classifier performs contrastive evaluation to distinguish genuine neologisms from slang, cultural borrowings, or jargon.

How do I classify language thought disorder segments in research datasets?

To classify language thought disorder segments in research datasets, submit speech fragments for automated neologism detection. The tool generates structured JSON annotations containing domain, severity, and exclusion checklists for consistent analysis.

Does automated neologism detection work on short clinical interview utterances?

Yes, automated neologism detection works on short clinical interview utterances. The classifier is specifically designed to evaluate brief speech fragments and label them as NEO or NO-NEO based on a provided evaluation rubric.

What output format do I get when classifying speech fragments for neologisms?

When classifying speech fragments for neologisms, you get a JSON object containing domain, severity, scratchpad, exclusion_checklist, and rationale fields. This structured output ensures consistent annotations for clinical research datasets.