use-case-specification
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.
Install
With your agent
Install OMGSkills skill "awslabs/agent-plugins:plugins/sagemaker-ai/skills/use-case-specification" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/awslabs/agent-plugins /tmp/agent-plugins && ln -s /tmp/agent-plugins/plugins/sagemaker-ai/skills/use-case-specification ~/.claude/skills/use-case-specificationFrom README
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 usecasespec.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.
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