gemini-cli-extensions/data-agent-kit-starter-pack

managing-python-dependencies

Ensures proper Python dependency management, avoiding global `pip install` and adhering to project-specific tooling. Use this skill if any of the following are true: 1. Attempting to run `pip install {package_name}`. 2. Python packages or dependencies need to be added or modified. 3. Initiating a new Python project. 4. Creating a new notebook, even if just using BigQuery cells. 5. Generating Python code that includes `import` statements for third-party libraries. 6. Before executing Python scri…

First seen Apr 28, 2026

Installation

$ npx skills add gemini-cli-extensions/data-agent-kit-starter-pack --skill managing-python-dependencies

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More details

Agent compatibility

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Repository health

Stars 179
License LICENSE
Default branch main
Open issues 3
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Versionv2
LicenseApache-2.0
Declared agents gemini
More metadata
version
v2
publisher
google

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,665 B
  • docs SUMMARY.md 608 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 13 installs

SKILL.md

Python Dependency Management Rule

[!CAUTION]

BEFORE any pip install: You MUST first detect the project's existing
dependency manager and use it correctly. Do NOT override the project's
established tooling.

[!NOTE]

Pre-Flight Environment Check Bundling: You MUST NOT run multiple
sequential 1-line shell check commands (e.g. separate commands for python
version, pyspark version, auth check, pip list). Combine all pre-flight
environment and package availability probes into a single composite python
one-liner or shell check step.

Example composite probe:

```bash
python3 -c "import sys, importlib.util; print(f'Python {sys.version.split()[0]}'); [(print(f'{pkg}: {import(pkg).version}') if importlib.util.find_spec(pkg) else print(f'{pkg}: not found')) for pkg in ['pyspark', 'google.cloud.bigquery']]"
```

This bundling also applies to dependency manager detection; use a single ls
or find command to check for all potential dependency manager configuration
and lock files at once (e.g. `ls uv.lock poetry.lock Pipfile.lock
requirements.txt pyproject.toml`).

Dependency Manager Detection

Before installing ANY Python package, check the workspace for these files in priority order:

  1. Signal: uv.lock or pyproject.toml with [tool.uv]

Tool: uv Install: uv add <package> * Setup: uv sync

  1. Signal: pyproject.toml with [tool.poetry]

Tool: Poetry Install: poetry add <package> * Setup: poetry install

  1. Signal: Pipfile

Tool: Pipenv Install: pipenv install <package> * Setup: pipenv install

  1. Signal: environment.yml

Tool: Conda Install: conda install <package> * Setup: conda env create -f environment.yml

  1. Signal: requirements.txt only

Tool: venv + pip Install: .venv/bin/pip install <package> * Setup: .venv/bin/pip install -r requirements.txt

  1. Signal: None of the above

Tool: venv + pip (default) Install: .venv/bin/pip install <package> * Setup: .venv/bin/pip install -r requirements.txt

Default: venv + pip

If no dependency manager is detected, use venv + pip + requirements.txt as the default:

# Initialize environment
python3 -m venv .venv

# Add dependencies
.venv/bin/pip install <package>

# Preserve state
.venv/bin/pip freeze > requirements.txt

Rules for venv + pip workflow:

  • Always use .venv/bin/pip or .venv/bin/python (explicit path).
  • After installing, run: .venv/bin/pip freeze > requirements.txt.
  • When setting up: .venv/bin/pip install -r requirements.txt.

Prohibited

  • NEVER run pip install globally
  • NEVER override an existing dependency manager with a different one