technology-stack-modernization-1-dependency-version-assessment
Sub-skill of technology-stack-modernization: 1. Dependency Version Assessment (+6).
Best use case
technology-stack-modernization-1-dependency-version-assessment is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Sub-skill of technology-stack-modernization: 1. Dependency Version Assessment (+6).
Teams using technology-stack-modernization-1-dependency-version-assessment should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/1-dependency-version-assessment/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How technology-stack-modernization-1-dependency-version-assessment Compares
| Feature / Agent | technology-stack-modernization-1-dependency-version-assessment | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Sub-skill of technology-stack-modernization: 1. Dependency Version Assessment (+6).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 1. Dependency Version Assessment (+6)
## 1. Dependency Version Assessment
**Process:**
1. Identify current dependency versions in project
2. Check for available updates on PyPI
3. Review CHANGELOG for breaking changes
4. Test compatibility with existing code
5. Update pyproject.toml with version constraints
**Version Update Checklist:**
```markdown
## Current Dependencies Review
| Package | Current | Latest | Breaking Changes? | Action |
|---------|---------|--------|-------------------|--------|
| pandas | 1.5.3 | 2.2.0 | Yes - deprecated methods | Update + refactor |
| numpy | 1.24.0 | 1.26.0 | No | Safe update |
| plotly | 5.14.0 | 5.18.0 | No | Safe update |
| click | 8.1.0 | 8.1.7 | No | Safe update |
## Update Strategy
1. **Safe updates** (no breaking changes): Batch update
2. **Breaking changes**: Update one at a time with testing
3. **Major versions**: Review migration guides first
4. **Test after each update**: Run full test suite
```
## 2. Deprecated Package Replacement
**Common Replacements:**
**Conda → UV (Package Manager)**
```bash
# Before (Conda)
conda create -n myenv python=3.11
conda activate myenv
conda install pandas numpy plotly
# After (UV) - workspace-hub standard
*See sub-skills for full details.*
## 3. Modern Python Features Adoption
**Python 3.11+ Features:**
**Type Hints and Generics**
```python
# Before (Python 3.9)
from typing import List, Dict, Optional
def process_data(items: List[str]) -> Dict[str, int]:
result: Dict[str, int] = {}
for item in items:
*See sub-skills for full details.*
## 4. pyproject.toml Modernization
**Complete Modern Configuration:**
```toml
[project]
name = "project-name"
version = "1.0.0"
description = "Project description"
requires-python = ">=3.11"
dependencies = [
# Data Processing (current versions)
"pandas>=2.0.0",
*See sub-skills for full details.*
## 5. Development Tools Update
**Pre-commit Hooks Configuration:**
```yaml
# .pre-commit-config.yaml
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.1.0
hooks:
- id: ruff
args: [--fix, --exit-non-zero-on-fix]
- id: ruff-format
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