qte77/implementing-python
plugins/python-dev/skills/implementing-python/SKILL.md
Implements concise, streamlined Python code matching exact architect specifications. Use when writing Python code, creating modules, or when the user asks to implement features in Python.
$ install --global
skillsauthnpx skillsauth add qte77/claude-code-plugins implementing-pythonInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 18, 2026, 2:50 AM50.7s2 files scanned
SKILL.md
- name:
- implementing-python
- description:
- Implements concise, streamlined Python code matching exact architect specifications. Use when writing Python code, creating modules, or when the user asks to implement features in Python.
- compatibility:
- Designed for Claude Code
- allowed-tools:
- Read, Grep, Glob, Edit, Write, Bash, WebSearch, WebFetch
- argument-hint:
- [feature-name]
- stability:
- stable
- content-hash:
- sha256:202611f850f48c0ffb59ba553331765e55a322c2242757f1e2d31ce0a9340f3a
- last-verified-cc-version:
- 1.0.34
Python Implementation
Target: $ARGUMENTS
Creates focused, streamlined Python implementations following architect specifications exactly. No over-engineering.
Python Standards
See references/python-best-practices.md for comprehensive Python guidelines.
Workflow
- Read architect specifications from provided documents
- Validate scope - Simple (100-200 lines) vs Complex (500+ lines)
- Study existing patterns in
src/structure - Implement minimal solution matching stated functionality
- Create focused tests matching task complexity
- Run
make validateand fix all issues
Implementation Strategy
Simple Tasks: Minimal functions, basic error handling, lightweight dependencies, focused tests
Complex Tasks: Class-based architecture, comprehensive validation, necessary dependencies, full test coverage
Always: Use existing project patterns, pass make validate
Output Standards
Simple Tasks: Minimal Python functions with basic type hints Complex Tasks: Complete modules with comprehensive testing All outputs: Concise, streamlined, no unnecessary complexity
Quality Checks
Before completing any task:
make validate
All type checks, linting, and tests must pass.
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