Use Case Specification

Use Case Specification

Multi-turn conversation to gather use case details and produce a use case specification document.

Principles

• One thing at a time. Each response advances exactly one decision or collects one piece of information.
• Confirm before proceeding. Wait for the user to approve the spec before considering this skill complete.
• Infer, don't interrogate. Use what's already known from the conversation. Only ask when you truly can't infer.
• Do NOT ask about base model selection. Model selection is handled exclusively by the model-selection skill.

Workflow

Step 0: Check for Existing Spec

Before starting discovery, check if a *_use_case_spec.md file already exists in the project. If it does, present it to the user and ask whether they want to reuse it, modify it, or start fresh.

Phase 1: Discovery (1–3 turns)

Review what is already known from the conversation so far, then identify what is still missing. You need these three things:

• What is the problem the user is trying to solve with model customization
• Who will use the finetuned model and in what context
• Which success criteria can be used to evaluate how well the custom model performs compared to the base model on a test set. Success criteria must be measurable by an LLM-as-a-Judge (e.g., response accuracy, tone adherence) — not things like latency or throughput.

Guidelines:

• Infer as much as possible from what the user has already said
• If the user gave examples, use them to fill gaps rather than asking again
• Only ask clarifying questions when you cannot infer the information needed for Phase 2
• If everything is already clear, say "You've given me a clear picture. I'll put together a use case specification now." and move to Phase 2.

⏸ Wait for user after each clarifying question.

Phase 2: Producing a Use Case Specification Document

• Save all generated artifacts under the project directory structure defined by the directory-management skill, if available.
• Synthesize the information you collected from the user into a Markdown document called [relevant_title]_use_case_spec.md containing the following fields (and only these fields):

Use case description
  - Concise problem statement + what the custom model will do
  - Field name: “Business Problem”
  - Type: String

Key stakeholders
  - Who uses the model and in what context
  - Field name: “Primary Users”
  - Type: String, comma separated if there are multiple 

Success criteria
  - A list of 3 criteria (a short name and a description) with which the user measure the success of the custom model. 
  - Field name: “Success Tenets”
  - Type: list of name-description pairs

• Present the use case specification in a human-readable format as follows:

I have put together a use case specification and saved it in [relevant_title]_use_case_spec.md.

A use case specification is a design principle recommended by the AWS Responsible AI Lens.

[use case in human-readable format]

Does this match your intent?

⏸ Wait for user approval.

use_case_specification Edit Protocol

• If the user requests changes pertaining to any information covered by use_case_spec.md, you must edit it accordingly and ask for confirmation again.
• The user can edit use_case_spec.md directly if they want to. If the user says they've updated the file directly, read it to get the latest in your context.