From sagemaker-ai
Creates project directory structure (specs/, scripts/, notebooks/, manifests/, agent_memory/) and resolves project naming. Used when starting or resuming a project or associating a PLAN.md.
How this skill is triggered — by the user, by Claude, or both
Slash command
/sagemaker-ai:directory-managementThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Before any work begins, resolve the project name:
Before any work begins, resolve the project name:
*/PLAN.md files in the current directory. If found, ask the user if they are resuming an existing project and load that PLAN.md into context.[a-z0-9-]), or ask directly if there isn't enough context. Present the recommended name and wait for user confirmation.Once project name is resolved:
<experiment-name>/ directory using the confirmed name for storing all the artifactsWhen working with the agent, all generated files are organized under an project directory.
<project-name>/
├── specs/
│ ├── PLAN.md # Your customization plan
├── scripts/ # Generated Python scripts
│ ├── <project-name>_transform_fn.py
├── notebooks/ # Generated Jupyter notebooks
│ ├── <project-name>.ipynb
├── manifests/ # Machine-readable outputs (JSON)
└── agent_memory/ # Session persistence (git-ignored)
└── session-notes.md # Progress, artifacts, next steps
npx claudepluginhub awslabs/agent-plugins --plugin sagemaker-aiCreates a date-organized workspace folder with static project docs and an assets directory for code, enabling other skills to operate with project context and daily work tracking.
Organizes project directories by mapping folders to work breakdowns or disposition rules, grouping files that change together. Use for repo layout, deciding file placement, or cleaning up messy folders.
Initializes new or existing projects for AI-assisted development: runs full-tree discovery, identifies domain, writes plan, generates artifacts, and reviews output end-to-end.