Use Case Specification

作者 awslabs097fe8ad56d8無授權條款915 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫今天更新

Creates a reusable use case specification file that defines the business problem, stakeholders, and measurable success criteria for model customization, as recommended by the AWS Responsible AI Lens. Use as the default first step in any model customization plan. Skip only if the user explicitly declines or already has a use case specification to reuse. Captures problem statement, primary users, and LLM-as-a-Judge success tenets.

AI 產生的概覽

透過多輪對話產出用於模型客製化的使用案例規格文件。

功能
透過簡短的探索式對話,蒐集模型客製化工作的業務問題、主要使用者,以及三項可衡量的成功標準。接著將這些內容寫入一個 Markdown 檔案,檔名由相關標題加上 _use_case_spec.md 後綴組成,並呈現該規格供使用者確認。它也會檢查是否已存在規格檔案,並詢問要沿用、修改或重新開始。
適用情境
適合作為模型客製化計畫的預設第一步,在模型選擇或訓練工作之前使用。只有在使用者明確拒絕,或已有可沿用的使用案例規格時才略過。
執行需求
不需要指令碼或特殊工具,僅為指示說明。若已有目錄管理技能提供的專案目錄結構則效果更好,並引用了 AWS Responsible AI Lens 的設計原則。

Use Case Specification

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

Principles

  1. One thing at a time. Each response advances exactly one decision or collects one piece of information.
  2. Confirm before proceeding. Wait for the user to approve the spec before considering this skill complete.
  3. Infer, don't interrogate. Use what's already known from the conversation. Only ask when you truly can't infer.
  4. 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

  1. Save all generated artifacts under the project directory structure defined by the directory-management skill, if available.
  2. 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
  1. 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.

來源與署名

來源:awslabs/agent-plugins位於plugins/sagemaker-ai/skills/use-case-specification提交097fe8a

授權條款: 無授權條款

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