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directory-management

Manages project directory setup and artifact organization. Use when starting a new project, resuming an existing one, or when a PLAN.md needs to be associated with a project directory. Creates the project folder structure (specs/, scripts/, notebooks/, manifests/, agent_memory/) and resolves project naming.

DevOps 与云915plugins/sagemaker-ai/skills/directory-management/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/awslabs/agent-plugins/directory-management/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Directory Management

Project Setup

Before any work begins, resolve the project name:

  1. If the project name is already known from conversation context, use it.
  2. Otherwise, scan for existing */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.
  3. If no existing projects are found, recommend a ≤64-char lowercase slug based on what you know from the conversation (only [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:

  1. Create and/or use the <experiment-name>/ directory using the confirmed name for storing all the artifacts

Directory Structure

When 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

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