agentic/code/frameworks/sdlc-complete/extensions/python/skills/venv-manager/SKILL.md
Create, manage, and validate Python virtual environments. Use for project isolation and dependency management.
npx skillsauth add jmagly/aiwg venv-managerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Single responsibility: Create and manage Python virtual environments for project isolation. (BP-4)
Before executing, VERIFY:
DO NOT create venv without confirming Python version.
ASK USER instead of guessing when:
NEVER delete existing venv without confirmation.
| Context Type | Included | Excluded | |--------------|----------|----------| | RELEVANT | Python version, project deps, venv path | Application code | | PERIPHERAL | CI/CD requirements | Test configurations | | DISTRACTOR | Deployment configs | Other language envs |
# Available Python versions
which python3
python3 --version
# Check for existing venv
ls -la venv/ 2>/dev/null || ls -la .venv/ 2>/dev/null || echo "No venv found"
# Current active environment
echo "VIRTUAL_ENV: $VIRTUAL_ENV"
# Standard creation
python3 -m venv venv
# With specific Python version
python3.11 -m venv venv
# With system packages access
python3 -m venv venv --system-site-packages
# Verify creation
ls -la venv/bin/python
# Activate
source venv/bin/activate
# Upgrade pip
pip install --upgrade pip
# Install from requirements.txt
pip install -r requirements.txt
# Or from pyproject.toml
pip install -e .
# Development dependencies
pip install -r requirements-dev.txt
# List installed packages
pip list
# Check for missing deps
pip check
# Export current state
pip freeze > requirements-lock.txt
On error:
venv creation failed → Check Python installationpip install failed → Check network, package availabilityactivation failed → Check shell compatibilitydependency conflict → Use pip-tools or poetryRollback command:
rm -rf venv && python3 -m venv venv
State saved to: .aiwg/working/checkpoints/venv-manager/
checkpoints/venv-manager/
├── python_version.txt # Python used
├── pip_freeze.txt # Installed packages
├── creation_log.txt # Creation output
└── validation_status.json # Health check results
| Command | Purpose |
|---------|---------|
| python3 -m venv venv | Create venv |
| source venv/bin/activate | Activate (bash/zsh) |
| venv\Scripts\activate | Activate (Windows) |
| deactivate | Deactivate |
| pip freeze > requirements.txt | Export deps |
| pip install -r requirements.txt | Install deps |
venv/ or .venv/ consistently.gitignorepip freeze or pip-toolsdata-ai
Report which research-corpus radar sidecars are overdue for refresh. Computes staleness (days since last refresh vs the cadence window) for every radar, sorted most-overdue-first. Runs via `aiwg corpus radar-status`.
data-ai
Aggregate research-corpus radar sidecars into a corpus or per-cluster freshness report — totals, overdue count, per-cluster / per-GRADE / per-trajectory breakdowns, an overdue table, and per-radar rationale snippets. Runs via `aiwg corpus radar-report`.
testing
Scaffold radar/freshness sidecars for research-corpus REFs. Pulls title/authors from the citation sidecar and GRADE from the analysis doc, defaults the refresh cadence from GRADE and the cluster from a corpus-local map, and stamps documentation/radar/REF-XXX-radar.md. Runs via `aiwg corpus radar-init`.
data-ai
Compute an entity's publication trajectory — per-year paper counts, topic drift, hot-streak detection (≥3 consecutive A-grade years), and career phase. Runs via `aiwg corpus profile-temporal`.