Concretism

Classify speech fragments as CON or NO-CON with a structured rationale.

Updated Nov 18, 2025

Search Tags:#CON #NO-CON #language-thought-disorder #linguistic-disorder #metaphor-interpretation #concretism #clinical-assessment

Ready to run

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

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables researchers and clinicians to efficiently classify speech fragments into Concretism (CON) or No Concretism (NO-CON), supporting standardized assessment of language thought disorders in transcripts.

Core Features & Use Cases

Automated fragment classification: determine whether a fragment expresses literal (concrete) versus abstract interpretation.
Clinical and research workflows: apply to interviews, assessments, and language samples to tag concreteness for analysis.
Use Case: given a transcript, label each utterance as CON or NO-CON to quantify concreteness across a dataset.

Quick Start

Analyze the fragment "Don't put all your eggs in one basket" and return CON or NO-CON.

Frequently Asked Questions about Concretism

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

FAQPage Schema

How do I classify speech fragments for concretism in clinical language samples?▼

To classify speech fragments for concretism, submit clinical language samples or transcripts to determine whether they exhibit literal versus abstract interpretation. The tool outputs a clear CON or NO-CON judgment along with a structured rationale.

What is concretism assessment in neuropsychological evaluations?▼

Concretism assessment in neuropsychological evaluations identifies whether a patient's speech fragments demonstrate concrete literal interpretation rather than abstract metaphor comprehension. It tags utterances as CON or NO-CON to quantify language thought disorders.

Can I use automated metaphor interpretation to tag concreteness across a research dataset?▼

Yes, you can apply automated metaphor interpretation to tag concreteness across research datasets by processing speech fragments from interviews and assessments. It labels each utterance as CON or NO-CON to quantify concreteness for analysis.

Does automated concretism classification work for language thought disorder transcripts?▼

Automated concretism classification supports standardized assessment of language thought disorders in transcripts by evaluating speech fragments. It determines whether fragments show literal concrete interpretation or abstract processing, returning a CON or NO-CON label.

What is the best way to quantify concreteness across a transcript dataset?▼

The best way to quantify concreteness across a transcript dataset is to label each utterance individually as CON or NO-CON. This automated fragment classification enables standardized analysis of concreteness across clinical and research language samples.

Why does concretism classification require a structured rationale for each fragment?▼

Concretism classification provides a structured scratchpad rationale for each fragment to ensure transparency in how literal versus abstract interpretation is evaluated. This supports reliable clinical assessment and research analysis of language thought disorders.