public-sample-workspace

To copy a public sample corpus into a local workspace, this skill materializes the tracked ICO and GCS data into the original_doc directory to provide a ready-to-test environment. It leverages the canonical sample preset to bootstrap a reproducible testing setup.

Yes, you can safely materialize a sample corpus into a non-empty original_doc directory because the skill includes safety checks that detect existing content. It requires explicit confirmation before overwriting any non-empty directories to prevent accidental data loss.

Local workspace bootstrapping with ICO and GCS data is the process of copying a tracked public sample corpus into a local original_doc folder. This creates a live, reproducible testing environment inside the canonical source repository for contributor validation.

Yes, you need shell or Python command execution to set up the local testing workspace because the skill requires local file access to copy corpus files. These execution environments handle the guided materialization and directory safety checks.

When the original_doc directory already contains files during sample corpus bootstrapping, a guard mechanism detects the existing content and pauses. The process requires your explicit confirmation before overwriting to ensure existing local files are protected.

Local corpus materialization requires explicit confirmation before overwriting to serve as a safety guard against unintended data loss. This precaution ensures contributors do not accidentally replace existing original_doc content during the workspace bootstrapping process.