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:
- Identify Target Working Directory:
- Confirm the root directory of the user's project workspace.
- 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/agentic_ecology (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:
agent_workspace/: Sandboxed folder for agent scripts, server.
databases/: Destination folder for Hoplite vector databases.
data/: Destination folder for raw datasets (e.g., audio, images).
- 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.
- 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, SQL log suppression filters, and
rules prohibiting Google copyright headers on generated workspace code).
- Synchronize Environment with
uv:
- Execute
uv sync from the target project root to create the local
virtual environment (.venv) and install all pinned dependencies.
- Verify Environment Setup:
- Execute the verification script
scripts/verify_env.py via uv run python to confirm that key libraries (perch_hoplite, speciesnet,
soundfile, tensorflow) import cleanly.
Technical Reference
For detailed command options, directory layout specifications, and verification
code snippets, see:
- Initialization Technical Reference
1---2name: agentic-ecology-init3description: Initializes a local uv-managed project directory for agentic ecology workloads. Sets up Python dependencies using reference pyproject.toml and uv.lock, configures workspace rules, and ensures Agentic Ecology skills are discoverable. Use when initializing a new project workspace or bootstrapping a clean environment.4license: Apache-2.05---67# Agentic Ecology Project Initialization Skill89Use this skill when you need to initialize a fresh, local project directory for10ecological modeling workflows (such as bioacoustics or camera trap analysis)11without cloning the entire `agentic_ecology` repository into the user's project12workspace.1314## Workflow Overview1516Follow these sequential steps to set up the local workspace:17181. **Identify Target Working Directory**:19 - Confirm the root directory of the user's project workspace.201. **Initialize Project & Scaffolding**:21 - Ensure the target project directory exists.22 - Run `uv init --python 3.12 --no-readme && rm main.py` in the project23 directory if it has not already been initialized. This pins24 `.python-version` to 3.12, generates `.gitignore`, initializes version25 control tracking, and removes the placeholder entrypoint.26 - Install the following skills locally with `npx skills add`:27 - `google-deepmind/agentic_ecology` (all skills).28 - `googlecolab/google-colab-cli` (`colab-operator` skill).29 - `googleworkspace/cli` (`gws-shared` and `gws-drive-upload` skills).30 - `google/skills` (`gcloud`, `google-cloud-storage-basics`, `google-cloud-storage-bucket-architect`, `google-cloud-storage-fuse`, and `cloud-logging-query-generation` skills).31 - Create standard working subdirectories:32 - `agent_workspace/`: Sandboxed folder for agent scripts, server.33 - `databases/`: Destination folder for Hoplite vector databases.34 - `data/`: Destination folder for raw datasets (e.g., audio, images).351. **Copy Reference Dependency Configurations**:36 - Overwrite the generated `pyproject.toml` and copy `uv.lock` from37 this skill's `assets/` directory into the target project root.38 - Adjust the package name in `pyproject.toml` to match the user's project39 name if desired, keeping all core dependencies (`perch-hoplite`,40 `speciesnet`), constraints, and build configurations intact.411. **Install Workspace Rules (`AGENTS.md`)**:42 - Copy the reference `AGENTS.md` from this skill's `assets/` directory43 into the appropriate location in the project workspace to establish44 standard Agentic Ecology guidelines (compute assessment and offloading45 protocols, macOS dynamic library deadlock rules, Linux46 PyTorch/TensorFlow import order rules, SQL log suppression filters, and47 rules prohibiting Google copyright headers on generated workspace code).481. **Synchronize Environment with `uv`**:49 - Execute `uv sync` from the target project root to create the local50 virtual environment (`.venv`) and install all pinned dependencies.511. **Verify Environment Setup**:52 - Execute the verification script `scripts/verify_env.py` via `uv run python` to confirm that key libraries (`perch_hoplite`, `speciesnet`,53 `soundfile`, `tensorflow`) import cleanly.5455## Technical Reference5657For detailed command options, directory layout specifications, and verification58code snippets, see:5960- [Initialization Technical Reference](references/REFERENCE.md)