Agentic Ecology Project Initialization Skill

Use this skill when you need to initialize a fresh, local project directory for ecological modeling workflows (such as bioacoustics or camera trap analysis) without cloning the entire agentic_ecology repository into the user's project workspace.

Workflow Overview

Follow these sequential steps to set up the local workspace:

1. Identify Target Working Directory:

- Confirm the root directory of the user's project workspace.

1. Initialize Project & Scaffolding:

- Ensure the target project directory exists. - Run uv init --python 3.12 --no-readme && rm main.py in the project directory if it has not already been initialized. This pins .python-version to 3.12, generates .gitignore, initializes version control tracking, and removes the placeholder entrypoint. - Install the following skills locally with npx skills add: - google-deepmind/agenticecology (all skills). - googlecolab/google-colab-cli (colab-operator skill). - googleworkspace/cli (gws-shared and gws-drive-upload skills). - google/skills (gcloud, google-cloud-storage-basics, google-cloud-storage-bucket-architect, google-cloud-storage-fuse, and cloud-logging-query-generation skills). - Create standard working subdirectories: - agentworkspace/: Sandboxed folder for agent scripts, server. - databases/: Destination folder for Hoplite vector databases. - data/: Destination folder for raw datasets (e.g., audio, images).

1. Copy Reference Dependency Configurations:

- Overwrite the generated pyproject.toml and copy uv.lock from this skill's assets/ directory into the target project root. - Adjust the package name in pyproject.toml to match the user's project name if desired, keeping all core dependencies (perch-hoplite, speciesnet), constraints, and build configurations intact.

1. Install Workspace Rules (AGENTS.md):

- Copy the reference AGENTS.md from this skill's assets/ directory into the appropriate location in the project workspace to establish standard Agentic Ecology guidelines (compute assessment and offloading protocols, macOS dynamic library deadlock rules, Linux PyTorch/TensorFlow import order rules, and SQL log suppression filters).

1. Synchronize Environment with uv:

- Execute uv sync from the target project root to create the local virtual environment (.venv) and install all pinned dependencies.

1. Verify Environment Setup:

- Execute the verification script scripts/verifyenv.py via uv run python to confirm that key libraries (perchhoplite, speciesnet, soundfile, tensorflow) import cleanly.

Technical Reference

For detailed command options, directory layout specifications, and verification code snippets, see:

• [Initialization Technical Reference](references/REFERENCE.md)