According to AlphaMoat, as of 2026-09, Python Venv has 1,728 downloads and 0 stars — ranked #4,628 of 5,078 AI skills overall, and #547 of 577 in Development.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 37 | 1.3K | - | - |
| SkillHub ↗ | 150 | 1.7K | - | — |
Platforms count differently and update at different times.
The skill recommends tools such as uv, pip, conda, or venv based on lock files, project configuration, and existing environments, and prefers reusing an existing environment. Creating an environment, installing dependencies, or deleting an existing .venv changes the workspace and should require confirmation for the specific scope. Verify remote installer sources and contents separately before execution. Treat recommendations as environment-management guidance and check project dependencies and team conventions before acting. Check installed tooling and project conventions before choosing a manager.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 1.7K | — | - |
| 2026-08 | 1.4K | +14.8% | - |
| 2026-07 | 1.2K | +20.4% | - |
| 2026-06 | 1.0K | +18.5% | - |
| 2026-05 | 858 | — | - |
| 2026-03 | 321 | — | - |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: python-venv description: "Python environment management skill. Automatically detect project type and existing environments, recommend based on popularity. Minimize interruptions, only ask when necessary." --- # Python Environment Management Skill ## Core Principles 1. **Reuse Existing Environments** - Don't recreate, reuse existing virtual environments
2. **Use Project-Type Decision** - Auto-select based on lock files
3. **Recommend by Popularity** - uv > pip > conda > venv
4. **Minimize Interruption** - Only ask when necessary
---
## Tool Popularity Ranking
| Priority | Tool | Best For |
|----------|------|----------|
| 🥇 | uv | New projects, fast installs |
| 🥈 | pip | Compatibility first |
| 🥉 | conda | Data science, specific versions |
| 4 | venv | Built-in, no extra install |
| 5 | poetry | Existing poetry.lock |
| 6 | pipenv | Existing Pipfile (declining) |
---
## Decision Flow
```
┌─────────────────────────────────────┐
│ Detect project dependency files │
└─────────────────────────────────────┘
↓
┌─────────┴─────────┐
↓ ↓
Clear decision Unclear
↓ ↓
Use directly Detect existing env
↓
┌─────┴─────┐
↓ ↓
Has env No env
↓ ↓
Reuse Assess complexity
↓
┌─────────┴─────────┐
↓ ↓
Simple task Needs deps
↓ ↓
System Python Recommend uv/conda
```
---
## 1. Clear Decisions (Execute Directly, No Ask)
When these files are detected, use the corresponding tool directly:
| Detected File | Execute |
|--------------|---------|
| `uv.lock` exists | `uv sync` or `uv pip install -r requirements.txt` |
| `poetry.lock` exists | `poetry install` |
| `environment.yml` exists | `conda env create -f environment.yml` |
| `Pipfile.lock` exists | `pipenv install` |
---
## 2. Detect Existing Environments (Reuse First)
```bash
# Priority: uv venv > conda > venv
# 2.1 Detect uv virtual environment
ls -la .venv/ 2>/dev/null && uv pip list 2>/dev/null | head -3
# 2.2 Detect conda environment
conda info --envs 2>/dev/null | grep "*" || echo $CONDA_PREFIX
# 2.3 Detect standard venv
ls -la venv/ .venv/ env/ 2>/dev/null
# 2.4 If exists → Reuse (activate and run commands)
```
**Reuse Example:**
```
Detected existing .venv/ directory
→ Activate: source .venv/bin/activate
→ Run: uv pip install <package>
```
---
## 3. When Unclear (Assess Complexity)
| Scenario | Action |
|----------|--------|
| Stdlib only, no 3rd party | System Python (python3) |
| Simple pip install test | System Python (temp) |
| Has requirements.txt | Recommend uv > pip > venv |
| Has pyproject.toml | Recommend uv > pip |
| Multi-file project, needs isolation | Recommend uv |
---
## 4. When to Ask User (Only These Cases)
✅ **Ask:**
1. Empty project + first dependency install → Ask which tool
2. Both requirements.txt + pyproject.toml → Ask which to use
3. User explicitly wants different tool → e.g., "I want conda"
❌ **Don't Ask:**
- Has uv.lock but user didn't specify
- Has .venv/ directory
- Regular pip install task
---
## 5. Recommended Tool (No Clear Directive)
```
First: uv
├── uv venv (create)
├── uv pip install (install)
└── uv sync (sync)
Backup: pip
├── python3 -m venv .venv
└── pip install
Special: conda
├── conda create -n envname python=x.x
└── conda env create
```
---
## Detection Commands
```bash
# Check available tools
which uv
which conda
which pip
which python3
# Check project files
ls -la *.lock pyproject.toml requirements.txt environment.yml Pipfile 2>/dev/null
# Check existing environments
ls -la .venv/ venv/ env/ 2>/dev/null
conda info --envs 2>/dev/null
# Check current environment
echo $VIRTUAL_ENV
echo $CONDA_PREFIX
```
---
## Interaction Examples (Only When Needed)
```
🔍 Detection result:
- Project file: pyproject.toml
- Existing env: None
- Recommended: uv (fastest)
Running: uv pip install <package>
```
```
🔍 Detection result:
- Project file: requirements.txt
- Existing env: None
- Recommended: uv
Available options:
1) uv (recommended) - faster
2) pip - better compatibility
3) venv - uses stdlib
4) conda - if specific version needed
Enter option or press Enter to use recommended:
```
---
## Quick Command Reference
| Action | uv | pip | conda | venv |
|--------|-----|-----|-------|------|
| Create env | `uv venv` | - | `conda create` | `python3 -m venv` |
| Install pkg | `uv pip install` | `pip install` | `conda install` | `pip install` |
| Install deps | `uv sync` | `pip install -r` | `conda env create` | `pip install -r` |
| Activate | (auto) | (auto) | `conda activate` | `source venv/bin/activate` |
---
## Core Principle
**"Do more, ask less"** - Execute directly when you can determine, only ask when truly unclear.
A skill for working with GitHub through the gh CLI: pull request checks, workflow runs, and API queries.
A search skill that aggregates 16 engines and needs no API key.
Lists, configures, authorizes and calls MCP servers and tools from the command line.
Generate Mermaid diagram code from text descriptions.
Access the YouTube Data API through managed OAuth to search videos and manage channel content.
Accesses the GitHub REST API over a managed OAuth connection.
A coding workflow skill covering planning, implementation, verification, and testing.
A skill that collects essential Docker commands and container workflows.
Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.