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Kikolo3000
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Poverty of Content of Speech

Classify speech fragments as POCS or NO-POCS with optional justification.

Updated Nov 18, 2025
Search Tags:#transcripts#text-classification#clinical-research#POCS#speech-analysis#NO-POCS
One-click install
npx skills add https://github.com/Kikolo3000/topsy_databaseprocessing-agent --skill poverty-of-content-of-speech
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Poverty of Content of Speech
Source: https://github.com/Kikolo3000/topsy_databaseprocessing-agent/tree/main/skills/POC
Command: npx skills add https://github.com/Kikolo3000/topsy_databaseprocessing-agent --skill poverty-of-content-of-speech

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

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

Core Features & Use Cases

  • Text-based classification: labels each fragment as POCS or NO-POCS with optional rationale.
  • Batch processing: accepts multiple fragments in a single run for research datasets.
  • Use Case: analyze transcripts from clinical interviews to identify fragments that show verbose yet content-poor speech patterns.

Quick Start

Provide one or more text fragments to be labeled. Example: "I spent the day thinking about relationships, but I can't explain why I feel uncertain." The skill returns a per-fragment label.

Frequently Asked Questions about Poverty of Content of Speech

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

FAQPage Schema
What is poverty of content of speech in language thought disorder assessment?▼

Poverty of content of speech (POCS) is a language thought disorder pattern where speech is verbose but conveys little meaningful information. This Skill classifies speech fragments into POCS or NO-POCS categories to support consistent clinical research analysis.

How do I classify clinical interview transcripts for speech analysis?▼

To classify clinical interview transcripts for speech analysis, provide single or multiple plain text fragments to this Skill. It processes the fragments and returns structured outputs with per-fragment POCS or NO-POCS labels and optional justification.

Can I process multiple speech fragments in one batch for research datasets?▼

Yes, you can process multiple speech fragments in one batch for research datasets. This Skill accepts multiple text fragments in a single run and returns structured outputs with per-fragment labels to streamline research data processing.

Does text classification for POCS return justification for the labels?▼

Yes, text classification for POCS returns optional justification for the labels. Along with the standard per-fragment POCS or NO-POCS classification, the Skill can provide the rationale supporting its assessment of the speech pattern.

What format does the speech classification output use?▼

The speech classification output uses a standard structured format such as JSON. This ensures the per-fragment POCS and NO-POCS labels and optional justifications are returned in a consistent, machine-readable structure for clinical research.

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