Clarify Requirements

Vague project briefs lead to wasted development cycles and endless rework. This skill stops you from guessing by systematically mapping a request into a decision tree, surfacing only the questions that require human intent before a single line of code is written.

What it does

• Decision Tree Mapping breaks down complex tasks into logical dependencies and sub-decisions.
• Frontier Questioning identifies and asks only the next set of questions that have all prerequisites met.
• Automated Fact-Checking ensures the agent searches files, paths, and environments first instead of bothering you with basic context.
• Tiered Recommendations provides a specific suggested answer for every question to speed up the approval process.
• Consensus Locking prevents development from starting until every critical decision path is confirmed.

How it works

1. Analyze the request to build a dependency map of necessary decisions.
2. Scan the local environment to resolve any factual variables automatically.
3. Prompt the user with a batch of "Frontier" questions—those at the current edge of the decision tree.
4. Iterate based on user feedback to unlock the next layer of dependent questions.

Frameworks & tools

This skill is framework-agnostic and functions within any CLI or IDE environment where an agent has read access to the local filesystem.

Why this beats prompting it yourself

Generic agents often dive into implementation with hidden assumptions, leading to "hallucinated" project structures. This skill enforces a structured inquiry phase that ensures the agent only asks what it cannot discover itself, reducing total interaction cycles.

Use cases

• Defining the architecture for a new multi-service system.
• Clarifying performance vs. readability trade-offs in a refactor.
• Gathering specific styling and behavior preferences for a UI component.

Known limitations

Does not support executing code during the questioning phase. Requires a clear initial user intent to begin mapping the decision tree.