clarifying-intent

Elicit intent and constraints from underspecified product requests into structured specs.

2|Updated Jan 28, 2026
One-click install
npx skills add https://github.com/chriswch/praxis --skill clarifying-intent
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: clarifying-intent
Source: https://github.com/chriswch/praxis/tree/main/skills/clarifying-intent
Command: npx skills add https://github.com/chriswch/praxis --skill clarifying-intent

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Underspecified requests from stakeholders lead to misaligned scope and wasted effort; this skill guides teams to a shared understanding by eliciting intent, constraints, unknowns, risks, and success criteria to produce precise artifacts.

Core Features & Use Cases

  • Elicit targeted clarifying questions to extract goals, constraints, risks, and acceptance criteria.
  • Generate a Feature Brief when the input is large, or a Story-Level Behavioral Spec for smaller work.
  • Provide structured handoffs to downstream workflows (e.g., slicing-stories) with clear acceptance criteria and scope.
  • Use templates and conventions from repository references to ensure consistency across teams.

Quick Start

Provide a vague requirement and the skill will ask targeted questions and generate a Feature Brief or Story-Level Behavioral Spec.

Frequently Asked Questions about clarifying-intent

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

FAQPage Schema
How do I turn vague product requests into actionable specs with acceptance criteria?▼

To turn vague product requests into actionable specs, you provide the raw requirement to elicit intent, constraints, and risks, generating a structured Story-Level Behavioral Spec with Given/When/Then acceptance criteria for shared understanding.

What is the best way to clarify underspecified requirements for large feature ideas?▼

The best way to clarify underspecified requirements for large features is to triage the input and generate a Feature Brief, which captures goals, unknowns, and constraints to hand off to downstream slicing-stories workflows.

How do I write a story spec that reduces ambiguity for development teams?▼

Writing a story spec that reduces ambiguity involves eliciting success criteria and constraints from underspecified tasks, directly producing a Story-Level Behavioral Spec with structured Given/When/Then acceptance criteria and handoff notes.

Can I use this approach for both large feature briefs and single tasks?▼

Yes, you can use this approach for both large feature briefs and single tasks, as it triages input scale to output either a Feature Brief for slicing-stories or a direct Story-Level Behavioral Spec with acceptance criteria.

When should I generate a Feature Brief instead of a Story-Level Behavioral Spec?▼

You should generate a Feature Brief instead of a Story-Level Behavioral Spec when the input is a large feature idea requiring slicing, whereas single smaller tasks directly produce a Story-Level Behavioral Spec with Given/When/Then criteria.