interrobang

Prompt AI assistants to ask clarifying questions before acting on ambiguous requests.

6|1|Updated Jun 23, 2026

Search Tags:#ai #prompting #assistant #error reduction #guess prevention

Ready to run

npx skills add https://github.com/JGalego/Bag-of-Tricks --skill interrobang

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: interrobang
Source: https://github.com/JGalego/Bag-of-Tricks/tree/main/interrobang
Command: npx skills add https://github.com/JGalego/Bag-of-Tricks --skill interrobang

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, re, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill ensures your AI assistant doesn't make assumptions, helping you avoid costly mistakes by prompting for clarity before acting.

Core Features & Use Cases

Clarifying Questions: Prompts your AI assistant to ask one sharp question before guessing when a request is ambiguous.
Detecting Guesses: Flags instances where the assistant should have asked a question but didn't.
Use Case: When working with complex data or high-stakes decisions, this Skill can prevent errors that might lead to financial loss or data breaches.

Quick Start

Run the interrobang skill on your latest transcript to check for potential guessing.

Frequently Asked Questions about interrobang

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

FAQPage Schema

How do I prevent my AI assistant from making assumptions with ambiguous prompts?▼

To prevent AI assistants from making assumptions, you can use prompting mechanisms that force the assistant to ask a clarifying question before acting. This approach detects ambiguity in requests and prompts for clarity to avoid costly errors in automated decision-making.

What is the best way to detect when an AI assistant should have asked a clarifying question?▼

Detecting when an AI assistant should have asked a clarifying question involves analyzing transcripts to flag instances where the assistant guessed instead of seeking clarity. This is achieved using Python and regex pattern matching to identify ambiguous prompts.

Do I need Python and regex to check my AI transcripts for guessing?▼

Yes, you need Python and regex to check AI transcripts for guessing. Python runs the analysis while regex handles the pattern matching required to detect ambiguity and flag instances where clarifying questions were missing.

Can I use prompt clarity checks for high-stakes data analysis and financial transactions?▼

Yes, you can use prompt clarity checks for high-stakes data analysis and financial transactions. Preventing assumptions in these scenarios avoids costly errors, data breaches, and financial loss by ensuring the assistant confirms ambiguous requests before execution.

How do I run a check on my latest AI transcript to find potential guessing?▼

To find potential guessing in your latest AI transcript, run the interrobang skill directly on the transcript file. It analyzes the text and flags instances where the assistant made a guess instead of asking a sharp clarifying question.

Does semantic analysis support optional LLMs for detecting ambiguity in prompts?▼

Yes, semantic analysis supports optional LLMs for detecting ambiguity in prompts. While Python and regex handle pattern matching, integrating an LLM provides deeper semantic analysis to evaluate the context and intent of the request.