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Requirements Clarification

Listed
youngger9765·vlatest·other

This skill clarifies ambiguous requirements by asking targeted questions, ensuring accurate understanding and preventing costly rework.

Install on your platform

This skill no longer installs under the name requirements-clarification. youngger9765/career_ios_backend is deleted or private, so it cannot be installed from.

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Repository install instructions

What we know about this skill

Publisher

youngger9765

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

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scanned

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Not scanned. repository not found or private Source recorded as youngger9765/career_ios_backend.
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About this skill

What it does

This skill helps clarify ambiguous or incomplete requirements. It can rephrase requests to be more specific, identify missing information needed for completion, and suggest alternative approaches based on potential interpretations of the initial request. The goal is to ensure a shared understanding before proceeding with any task.

When to use it

  • When a user's instructions are vague or open-ended (e.g., "Write some code").
  • Before starting a complex project where misunderstandings could lead to wasted effort.
  • To proactively identify potential issues in requirements documents before development begins.
  • When dealing with stakeholders who may not be technical and have difficulty articulating their needs precisely.

Key capabilities

  • Requirement rephrasing
  • Missing information identification
  • Alternative approach suggestion
  • Ambiguity resolution

Example prompts

  • "Can you clarify what 'some code' means for this project?"
  • "I need a report on sales data. What specific time period and metrics should I include?"
  • “The requirements say ‘user authentication’. Can you help me break that down into more detailed steps?”

Tips & gotchas

This skill is most effective when used early in a process, before significant work has begun. It relies on the AI agent's ability to understand natural language and infer intent; complex or highly technical requirements may still require human review.