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Get Started Free →awslabs/directory-management
Manages project directory setup and artifact organization.
Passed 17 of 22 test cases with the skill, and 6 of 22 without it.
and 20 more in the full report
11 fixed6 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 11 test cases the skill fixed. Same model, same prompt, with and without the skill.
For a confirmed project named 'etl-cleaner', what exact filename is assigned to the Python script in `scripts/`?
| Checked | Without skill | With skill |
|---|---|---|
| Names the Python script file `etl-cleaner_transform_fn.py`. | Missed | Passed |
The instructions your model reads when the skill loads.
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
test cases passed, vs 6 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.