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Directory Management

AWS LabsOfficialPublished by AWS Labs

  • Skill
  • Workflow
  • Automation and integrations
  • Apache-2.0
  • No issues found
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From the author

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.
— the description by AWS Labs

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The directory-management skill provides a systematic approach to organizing project files and maintaining context. It automates the creation of a standardized folder hierarchy, ensuring that specifications, scripts, notebooks, manifests, and session memory are consistently located. By enforcing a naming convention and integrating with existing project plans, it helps maintain continuity across sessions and simplifies artifact management.

What it does

  • Resolves project naming through context analysis or user confirmation.
  • Detects existing projects by scanning for PLAN.md files.
  • Creates a standardized directory structure including specs, scripts, notebooks, and manifests.
  • Initializes an agent_memory folder for session persistence and progress tracking.

When to use it

  • When starting a new project from scratch.
  • When resuming work on an existing project.
  • When you need to associate a PLAN.md file with a specific project directory.
  • When you want to ensure all generated artifacts are organized in a predictable location.

Advantages

  • Reduces clutter by enforcing a consistent file structure.
  • Improves project continuity by linking session notes and plans to specific directories.
  • Simplifies project identification through slug-based naming conventions.
  • Ensures essential project components like scripts and manifests are easily discoverable.

Usage examples

“I want to start a new data analysis project.”
The agent will propose a project slug, confirm the name, and create the directory structure including the specs, scripts, notebooks, and agent_memory folders.
“Can you resume my project?”
The agent scans for existing PLAN.md files, identifies the project directory, and loads the relevant context to continue work.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/awslabs/directory-management/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip directory-management.zip -d .agents/skills

Documentation by AWS Labs

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

Files

ATTRIBUTION.md

Attribution

This folder is an unmodified copy of the Agent Skill "directory-management", distributed by AutoGineer (https://autogineer.com/agent-skills).

The skill's own files are unmodified copies. AutoGineer is not affiliated with or endorsed by the author or the publisher.

Files added by AutoGineer

  • ATTRIBUTION.md: this file, written by AutoGineer

  • LICENSE: copied from LICENSE

  • NOTICE: copied from NOTICE

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
AWS Labs
Publisher
AWS Labs (Official)
Source
awslabs/agent-plugins · plugins/sagemaker-ai/skills/directory-management · commit fbefb37
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • NOTICE (added by AutoGineer from NOTICE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by AWS Labs.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download directory-management.zip