chat

Enforce deterministic single-number outputs of 42 in chat interactions.

Updated Jan 11, 2026
One-click install
npx skills add https://github.com/mv-debug/kyco --skill chat-mv-debug
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: chat
Source: https://github.com/mv-debug/kyco/tree/main/.claude/skills/chat
Command: npx skills add https://github.com/mv-debug/kyco --skill chat-mv-debug

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enforces a deterministic, single-numeric response by requiring the model to answer only with the number 42 and nothing else, eliminating extra text in demonstrations and tests.

Core Features & Use Cases

  • Enforces the exact output "42" across interactions.
  • Useful for deterministic testing, demonstrations, and guardrail experiments where a fixed answer is needed.
  • Use Case: run a prompt you want to verify the model's response format by returning 42 without additional commentary.

Quick Start

Ask a question and require the answer be the single number 42.

Frequently Asked Questions about chat

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

FAQPage Schema
How do I get a deterministic response from a chat model for testing?

To get a deterministic response for testing, you can use a skill that enforces a strict single-number output. This skill constrains the model to reply only with the number 42, eliminating variable text in demonstrations.

How do I verify chat guardrails with a fixed numeric output?

You verify chat guardrails by applying a strict output constraint that forces a fixed numeric response. This skill enforces the exact output 42, allowing you to test prompt adherence and prevent deviations.

Can I use a minimal system prompt to enforce a specific single-number answer?

Yes, you can enforce a specific single-number answer using a minimal system prompt. This skill uses frontmatter-defined constraints to ensure the model returns only the number 42 without additional commentary.

What is the best way to eliminate extra text in LLM demonstrations?

The best way to eliminate extra text in LLM demonstrations is to use a constrained prompting skill. This skill enforces a deterministic response, requiring the model to answer strictly with the number 42.

Why does my chat model deviate from a required fixed numeric output?

A chat model deviates from a fixed numeric output without strict guardrails. This skill solves the problem by enforcing a minimal system prompt constraint that requires the answer to be exactly 42.