// Execute Python code locally with marketplace API access for 90%+ token savings on bulk operations. Activates when user requests bulk operations (10+ files), complex multi-step workflows, iterative processing, or mentions efficiency/performance.
Generate multiple diverse solutions in parallel and select the best. Use for architecture decisions, code generation with multiple valid approaches, or creative tasks where exploring alternatives improves quality.
Perform bulk code refactoring operations like renaming variables/functions across files, replacing patterns, and updating API calls. Use when users request renaming identifiers, replacing deprecated code patterns, updating method calls, or making consistent changes across multiple locations.
Transfer code between files with line-based precision. Use when users request copying code from one location to another, moving functions or classes between files, extracting code blocks, or inserting code at specific line numbers.
Analyze files and get detailed metadata including size, line counts, modification times, and content statistics. Use when users request file information, statistics, or analysis without modifying files.
Break down feature requests into detailed, implementable plans with clear tasks. Use when user requests a new feature, enhancement, or complex change.
Stage, commit, and push git changes with conventional commit messages. Use when user wants to commit and push changes, mentions pushing to remote, or asks to save and push their work. Also activates when user says "push changes", "commit and push", "push this", "push to github", or similar git workflow requests.
| name | code-execution |
| description | Execute Python code locally with marketplace API access for 90%+ token savings on bulk operations. Activates when user requests bulk operations (10+ files), complex multi-step workflows, iterative processing, or mentions efficiency/performance. |
Execute Python locally with API access. 90-99% token savings for bulk operations.
Use direct Python imports in Claude Code:
from execution_runtime import fs, code, transform, git
# Code analysis (metadata only!)
functions = code.find_functions('app.py', pattern='handle_.*')
# File operations
code_block = fs.copy_lines('source.py', 10, 20)
fs.paste_code('target.py', 50, code_block)
# Bulk transformations
result = transform.rename_identifier('.', 'oldName', 'newName', '**/*.py')
# Git operations
git.git_add(['.'])
git.git_commit('feat: refactor code')
If not installed: Run ~/.claude/plugins/marketplaces/mhattingpete-claude-skills/execution-runtime/setup.sh
fs): copy_lines, paste_code, search_replace, batch_copycode): find_functions, find_classes, analyze_dependencies - returns METADATA only!transform): rename_identifier, remove_debug_statements, batch_refactorgit): git_status, git_add, git_commit, git_pushBulk refactor (50 files):
from execution_runtime import transform
result = transform.rename_identifier('.', 'oldName', 'newName', '**/*.py')
# Returns: {'files_modified': 50, 'total_replacements': 247}
Extract functions:
from execution_runtime import code, fs
functions = code.find_functions('app.py', pattern='.*_util$') # Metadata only!
for func in functions:
code_block = fs.copy_lines('app.py', func['start_line'], func['end_line'])
fs.paste_code('utils.py', -1, code_block)
result = {'functions_moved': len(functions)}
Code audit (100 files):
from execution_runtime import code
from pathlib import Path
files = list(Path('.').glob('**/*.py'))
issues = []
for file in files:
deps = code.analyze_dependencies(str(file)) # Metadata only!
if deps.get('complexity', 0) > 15:
issues.append({'file': str(file), 'complexity': deps['complexity']})
result = {'files_audited': len(files), 'high_complexity': len(issues)}
✅ Return summaries, not data ✅ Use code_analysis (returns metadata, not source) ✅ Batch operations ✅ Handle errors, return error count
❌ Don't return all code to context ❌ Don't read full source when you need metadata ❌ Don't process files one by one
| Files | Traditional | Execution | Savings |
|---|---|---|---|
| 10 | 5K tokens | 500 | 90% |
| 50 | 25K tokens | 600 | 97.6% |
| 100 | 150K tokens | 1K | 99.3% |