Use Case Specification
by awslabs097fe8ad56d8No license915 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated today
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.
Add to a SourceWeft workspace
- Open the skill in your dashboard and add it to a workspace.
- Enable it for the chats that should use it.
This skill is instructions only: it ships no scripts to execute.
Add to SourceWeftYou will be asked to sign in first, then taken straight to this skill.
Ask your agent to install it
Paste this prompt into Claude Code, Codex, Cursor or another agent that can run commands — or into SourceWeft chat. The agent reads this skill's install guide, shows you its source, license and scripts, and installs it with the SourceWeft CLI once you agree.
Read https://sourceweft.com/skills/gh-awslabs-agent-plugins-use-case-specification/install.md and install the skill it describes. Before installing, show me its source, license and whether it ships scripts, and wait for my OK. Ask me before changing anything else on my machine.Install it yourself from a terminal
For Claude Code, Codex, Cursor and other local agents. The SourceWeft CLI fetches the skill from its source repository at the commit scanned here, and verifies every file against the hashes recorded when the skill was scanned. If anything differs, nothing is written.
npx @sourceweft/cli skills install gh-awslabs-agent-plugins-use-case-specificationAdd --agent claude-code, codex, cursor or universal to choose which agent gets it (Claude Code by default).
Upstream installer — not verified by SourceWeft
The open-source skills installer fetches the same pinned commit, but does not check the files against the hashes SourceWeft recorded.
npx skills add https://github.com/awslabs/agent-plugins/tree/097fe8ad56d8a1d5e2c81d7880adf145553cf244/plugins/sagemaker-ai/skills/use-case-specificationSource and attribution
Source:awslabs/agent-pluginsinplugins/sagemaker-ai/skills/use-case-specificationat commit097fe8a
License: No license
Content belongs to its original authors. SourceWeft indexes it from a public repository.
More from awslabs/agent-plugins
Sdk Getting Started
awslabs
Preflight checks that verify the environment for SageMaker AI operations, including SDK version, AWS region, and execution role.
Planning
awslabs
Guides intent discovery and produces a step-by-step plan for model customization workflows, saving it as PLAN.md.
Directory Management
awslabs
Sets up and organizes a project directory structure and resolves project naming before work begins.
Aws Step Functions
awslabs
Guides authoring AWS Step Functions state machines in Amazon States Language with JSONata.
Aws Serverless Deployment
awslabs
Guides AWS SAM and CDK deployment of serverless applications, covering scaffolding, IaC templates, constructs, and CI/CD.
Aws Lambda Microvms
awslabs
Guides building, running, and operating applications on AWS Lambda MicroVMs, including images, lifecycle hooks, tokens, and networking.
More in AI & Agents
Skill Development
anthropics
Guides creation of Claude Code plugin skills, covering structure, descriptions, progressive disclosure and validation.
Plugin Structure
anthropics
Guides the structure, manifest, and component layout of Claude Code plugins.
Command Development
anthropics
Guides creation of Claude Code slash commands, covering structure, YAML frontmatter, arguments and plugin features.
Claude Md Improver
anthropics
Audits CLAUDE.md files in a repository, scores their quality, and applies approved targeted improvements.
Google Cloud Solution Agentic Ai Data Science Workflow
Guides design of a multi-product agentic data science architecture on Google Cloud, from requirements to deployment and validation.
Google Cloud Solution Agentic Ai Borderless Data Lakehouse
Guides design of a borderless multicloud open data lakehouse on Google Cloud, from requirements discovery to deployment and validation.