# How Skill Scripts Are Copied Into the Workspace and Made Available to Agents in Harvey-Labs > Learn how Harvey-Labs copies skill scripts into a workspace and makes them available to agents for bash execution. Discover the process of exposing scripts via mounted sandbox directories. - Repository: [Harvey/harvey-labs](https://github.com/harveyai/harvey-labs) - Tags: internals - Published: 2026-08-11 --- **Harvey-Labs copies skill scripts into an isolated per-run workspace using `shutil.copytree` and exposes them to agents via a mounted sandbox directory, enabling direct bash execution during evaluation runs.** The harveyai/harvey-labs framework equips LLM-driven agents with reusable utilities for processing complex file formats like Excel, Word, and PowerPoint. To ensure each evaluation run operates within a clean, reproducible environment, the system automatically **copies skill scripts into the workspace** before mounting that directory into the execution sandbox. ## Skill Resolution and Workspace Initialization Before any files are copied, the framework determines which skills are required for the current evaluation run. This logic resides in the `main()` function within [[`harness/run.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py)](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py). ### Determining the Skill List The system checks for the optional `--skills` command-line argument. When omitted, it defaults to loading **all** skills defined in `DEFAULT_SKILLS`. When provided, only the specified comma-separated skills are loaded. This resolution occurs at lines 86-89 of [`harness/run.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py), where the skill list is parsed and normalized before proceeding to workspace setup. ### Creating the Per-Run Workspace For complete isolation between runs, the framework generates a fresh workspace directory at `results//workspace`. This directory serves as the mount point for the sandbox and the destination for all copied skill scripts. The path construction happens at lines 82-85 of [`harness/run.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py): ```python results_dir = Path("results") / args.run_id workspace_dir = results_dir / "workspace" workspace_dir.mkdir(parents=True, exist_ok=True) ``` This ensures that `workspace_dir` exists and is empty for every new evaluation. ## The Mechanism for Copying Skill Scripts Into the Workspace Once the workspace exists, the framework invokes `setup_skill_scripts()` to populate it with utility files from the requested skill packages. ### The setup_skill_scripts Implementation Located at lines 17-24 of [`harness/run.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py), this function iterates over the resolved skill list and copies the entire `scripts/` subdirectory from each skill package into the workspace. The implementation uses `shutil.copytree` with `dirs_exist_ok=True` to handle overwrites gracefully: ```python def setup_skill_scripts(workspace_dir: Path, skills: List[str]) -> None: skills_dir = workspace_dir / "skills" for skill in skills: src = Path("harness/skills") / skill / "scripts" dst = skills_dir / skill / "scripts" shutil.copytree(src, dst, dirs_exist_ok=True) ``` This operation places scripts at `workspace/skills//scripts/`, maintaining the original directory structure from the source repository. ### Source and Destination Paths The source scripts live within the repository under `harness/skills//scripts/`. For example: - [`harness/skills/xlsx/scripts/validate.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/skills/xlsx/scripts/validate.py) - [`harness/skills/docx/scripts/template_fill.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/skills/docx/scripts/template_fill.py) After copying, these become available at: - `results//workspace/skills/xlsx/scripts/validate.py` - `results//workspace/skills/docx/scripts/template_fill.py` ## How Agents Access Copied Skill Scripts After the copy operation completes, the framework starts the sandbox environment via [[`sandbox/sandbox.py`](https://github.com/harveyai/harvey-labs/blob/main/sandbox/sandbox.py)](https://github.com/harveyai/harvey-labs/blob/main/sandbox/sandbox.py). The sandbox mounts the `workspace` directory, making the copied skill scripts directly accessible to the agent as ordinary filesystem utilities. ### Executing Scripts Inside the Sandbox The agent invokes these scripts using standard bash commands executed through the sandbox's `ToolExecutor`. Because the workspace is mounted as the working directory, scripts are referenced by their relative path: ```bash bash skills/xlsx/scripts/validate.py input.xlsx bash skills/docx/scripts/template_fill.py template.md data.json ``` This design decouples the agent from the host filesystem while providing full access to the isolated skill utilities within the container. ## Running Evaluations with Custom Skill Sets You can control which skill scripts are copied into the workspace using the `--skills` flag. ### Running with Default Skills To automatically copy **all** default skill scripts: ```bash python -m harvey_labs.harness.run \ --model claude-sonnet-5 \ --task corporate-ma/review-data-room-red-flag-review \ --run-id myrun123 ``` ### Running with Specific Skills To copy only the `xlsx` and `docx` skill scripts: ```bash python -m harvey_labs.harness.run \ --model claude-sonnet-5 \ --task corporate-ma/review-data-room-red-flag-review \ --run-id myrun456 \ --skills xlsx docx ``` In both cases, the agent can execute commands like: ```bash bash skills/xlsx/scripts/validate.py data.xlsx ``` ## Summary - **Skill resolution** occurs in [`harness/run.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py) (lines 86-89), defaulting to `DEFAULT_SKILLS` unless the `--skills` flag is provided. - **Workspace creation** happens at `results//workspace` (lines 82-85 of [`harness/run.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py)), ensuring isolated execution environments. - **Script copying** is handled by `setup_skill_scripts()` (lines 17-24) using `shutil.copytree(..., dirs_exist_ok=True)` to populate `workspace/skills//scripts/`. - **Agent access** is granted through sandbox mounting, allowing bash execution of scripts via relative paths like [`skills/xlsx/scripts/validate.py`](https://github.com/harveyai/harvey-labs/blob/main/skills/xlsx/scripts/validate.py). ## Frequently Asked Questions ### Where are skill scripts copied within the workspace? Skill scripts are copied to `results//workspace/skills//scripts/`. This structure mirrors the source location in `harness/skills//scripts/` and is created automatically by the `setup_skill_scripts()` function in [`harness/run.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py). ### How does the agent execute copied skill scripts? The agent executes scripts by invoking bash commands with relative paths from the workspace root, such as `bash skills/xlsx/scripts/validate.py`. The sandbox mounts the workspace directory, so these commands execute inside the container with full access to the copied utilities. ### What happens if script directories already exist in the workspace? The `setup_skill_scripts()` function uses `shutil.copytree(..., dirs_exist_ok=True)`, which overwrites existing files without raising errors. This ensures that each run starts with fresh copies of the skill scripts even if the workspace directory already contains data from previous operations. ### Can I specify which skills to copy when running an evaluation? Yes. Pass the `--skills` flag followed by space-separated skill names to the run command. If omitted, the system uses `DEFAULT_SKILLS` to copy all available skill scripts. This logic is implemented in the argument parsing section of `main()` in [`harness/run.py`](https://github.com/harveyai/harvey-labs/blob/main/harness/run.py).