Verbigeration

Classify speech fragments as VERB or NO-VERB using provided criteria.

Updated Nov 18, 2025

Search Tags:#transcripts #VER #verbigeration #speech-analysis #psycholinguistics #clinical-assessment

Ready to run

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

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps clinicians and researchers automatically identify verbigeration episodes in speech transcripts, reducing manual review time and improving adjudication consistency.

Core Features & Use Cases

Automated VER/NO-VERB classification on interview fragments to support clinical scoring.
Scratchpad-guided evaluation with a structured rationale, severity estimation, and exclusion criteria.
Use Case: Analyze interview transcripts to quantify verbigeration frequency and severity across cohorts.

Quick Start

Classify the following fragment as VERB or NO-VERB: S: Nothing...nothing...nothing...nothing...nothing.

Frequently Asked Questions about Verbigeration

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

FAQPage Schema

How do I detect verbigeration in speech transcripts?▼

Detect verbigeration in speech transcripts by classifying fragments as VERB or NO-VERB using repetition thresholds and scratchpad rules across contexts. This automated evaluation returns a structured rationale and severity score to support clinical assessment.

What is verbigeration in clinical psycholinguistics?▼

Verbigeration in clinical psycholinguistics is the pathological repetition of words or phrases in speech. This Skill identifies these episodes in interview fragments by applying clinical criteria to determine if the speech qualifies as VERB.

How do I classify speech fragments for verbigeration severity?▼

Classify speech fragments for verbigeration severity by evaluating the repetition threshold against the last interviewer utterance. The Skill generates a severity score and rationale while applying exclusion criteria to ensure accurate clinical assessment.

Can I automate verbigeration frequency analysis across interview cohorts?▼

Automate verbigeration frequency analysis across cohorts by processing interview transcripts to label episodes VERB or NO-VERB. The structured evaluation yields quantifiable frequency and severity metrics for clinical research.

Does verbigeration detection require the last interviewer utterance?▼

Verbigeration detection requires the last interviewer utterance as a criterion to contextualize the speech fragment. Applying this contextual baseline ensures the scratchpad rules accurately differentiate between VERB and NO-VERB classifications.