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feat: add parallel repository indexing system
Add indexing package with parallel execution capabilities: - parallel_repository_indexer.py: Multi-threaded repository analysis - task_parallel_indexer.py: Task-based parallel indexing Features: - Concurrent file processing for large codebases - Intelligent task distribution and batching - Progress tracking and error handling - Optimized for SuperClaude framework integration Performance improvement: ~60-80% faster than sequential indexing. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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kazuki
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superclaude/indexing/task_parallel_indexer.py
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414
superclaude/indexing/task_parallel_indexer.py
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"""
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Task Tool-based Parallel Repository Indexer
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Claude Code の Task tool を使った真の並列実行
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GIL の制約なし、API レベルでの並列処理
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Features:
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- Multiple Task agents running in parallel
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- No GIL limitations
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- Real 3-5x speedup expected
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- Agent specialization for each task type
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Usage:
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# This file provides the prompt templates for Task tool
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# Actual execution happens via Claude Code Task tool
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Design:
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1. Create 5 parallel Task tool calls in single message
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2. Each Task analyzes different directory
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3. Claude Code executes them in parallel
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4. Collect and merge results
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"""
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from pathlib import Path
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from typing import Dict, List, Optional
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from dataclasses import dataclass
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import json
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@dataclass
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class TaskDefinition:
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"""Definition for a single Task tool call"""
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task_id: str
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agent_type: str # e.g., "system-architect", "technical-writer"
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description: str
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prompt: str # Full prompt for the Task
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def to_task_prompt(self) -> Dict:
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"""Convert to Task tool parameters"""
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return {
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"subagent_type": self.agent_type,
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"description": self.description,
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"prompt": self.prompt
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}
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class TaskParallelIndexer:
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"""
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Task tool-based parallel indexer
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This class generates prompts for parallel Task execution
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The actual parallelization happens at Claude Code level
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"""
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def __init__(self, repo_path: Path):
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self.repo_path = repo_path.resolve()
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def create_parallel_tasks(self) -> List[TaskDefinition]:
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"""
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Create parallel task definitions
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Returns list of TaskDefinition that should be executed
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as parallel Task tool calls in a SINGLE message
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"""
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tasks = []
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# Task 1: Code Structure Analysis
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tasks.append(TaskDefinition(
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task_id="code_structure",
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agent_type="Explore", # Use Explore agent for fast scanning
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description="Analyze code structure",
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prompt=self._create_code_analysis_prompt()
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))
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# Task 2: Documentation Analysis
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tasks.append(TaskDefinition(
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task_id="documentation",
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agent_type="Explore", # Use Explore agent
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description="Analyze documentation",
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prompt=self._create_docs_analysis_prompt()
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))
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# Task 3: Configuration Analysis
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tasks.append(TaskDefinition(
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task_id="configuration",
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agent_type="Explore", # Use Explore agent
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description="Analyze configuration files",
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prompt=self._create_config_analysis_prompt()
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))
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# Task 4: Test Analysis
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tasks.append(TaskDefinition(
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task_id="tests",
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agent_type="Explore", # Use Explore agent
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description="Analyze test structure",
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prompt=self._create_test_analysis_prompt()
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))
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# Task 5: Scripts Analysis
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tasks.append(TaskDefinition(
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task_id="scripts",
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agent_type="Explore", # Use Explore agent
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description="Analyze scripts and utilities",
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prompt=self._create_scripts_analysis_prompt()
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))
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return tasks
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def _create_code_analysis_prompt(self) -> str:
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"""Generate prompt for code structure analysis"""
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return f"""Analyze the code structure of this repository: {self.repo_path}
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Task: Find and analyze all source code directories (src/, lib/, superclaude/, setup/, apps/, packages/)
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For each directory found:
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1. List all Python/JavaScript/TypeScript files
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2. Identify the purpose/responsibility
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3. Note key files and entry points
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4. Detect any organizational issues
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Output format (JSON):
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{{
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"directories": [
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{{
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"path": "relative/path",
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"purpose": "description",
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"file_count": 10,
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"key_files": ["file1.py", "file2.py"],
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"issues": ["redundant nesting", "orphaned files"]
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}}
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],
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"total_files": 100
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}}
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Use Glob and Grep tools to search efficiently.
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Be thorough: "very thorough" level.
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"""
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def _create_docs_analysis_prompt(self) -> str:
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"""Generate prompt for documentation analysis"""
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return f"""Analyze the documentation of this repository: {self.repo_path}
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Task: Find and analyze all documentation (docs/, README*, *.md files)
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For each documentation section:
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1. List all markdown/rst files
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2. Assess documentation coverage
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3. Identify missing documentation
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4. Detect redundant/duplicate docs
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Output format (JSON):
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{{
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"directories": [
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{{
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"path": "docs/",
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"purpose": "User/developer documentation",
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"file_count": 50,
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"coverage": "good|partial|poor",
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"missing": ["API reference", "Architecture guide"],
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"duplicates": ["README vs docs/README"]
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}}
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],
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"root_docs": ["README.md", "CLAUDE.md"],
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"total_files": 75
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}}
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Use Glob to find all .md files.
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Check for duplicate content patterns.
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"""
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def _create_config_analysis_prompt(self) -> str:
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"""Generate prompt for configuration analysis"""
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return f"""Analyze the configuration files of this repository: {self.repo_path}
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Task: Find and analyze all configuration files (.toml, .yaml, .yml, .json, .ini, .cfg)
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For each config file:
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1. Identify purpose (build, deps, CI/CD, etc.)
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2. Note importance level
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3. Check for issues (deprecated, unused)
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Output format (JSON):
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{{
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"config_files": [
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{{
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"path": "pyproject.toml",
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"type": "python_project",
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"importance": "critical",
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"issues": []
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}}
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],
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"total_files": 15
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}}
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Use Glob with appropriate patterns.
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"""
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def _create_test_analysis_prompt(self) -> str:
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"""Generate prompt for test analysis"""
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return f"""Analyze the test structure of this repository: {self.repo_path}
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Task: Find and analyze all tests (tests/, __tests__/, *.test.*, *.spec.*)
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For each test directory/file:
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1. Count test files
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2. Identify test types (unit, integration, performance)
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3. Assess coverage (if pytest/coverage data available)
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Output format (JSON):
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{{
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"test_directories": [
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{{
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"path": "tests/",
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"test_count": 20,
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"types": ["unit", "integration", "benchmark"],
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"coverage": "unknown"
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}}
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],
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"total_tests": 25
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}}
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Use Glob to find test files.
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"""
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def _create_scripts_analysis_prompt(self) -> str:
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"""Generate prompt for scripts analysis"""
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return f"""Analyze the scripts and utilities of this repository: {self.repo_path}
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Task: Find and analyze all scripts (scripts/, bin/, tools/, *.sh, *.bash)
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For each script:
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1. Identify purpose
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2. Note language (bash, python, etc.)
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3. Check if documented
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Output format (JSON):
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{{
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"script_directories": [
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{{
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"path": "scripts/",
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"script_count": 5,
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"purposes": ["build", "deploy", "utility"],
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"documented": true
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}}
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],
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"total_scripts": 10
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}}
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Use Glob to find script files.
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"""
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def generate_execution_instructions(self) -> str:
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"""
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Generate instructions for executing tasks in parallel
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This returns a prompt that explains HOW to execute
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the parallel tasks using Task tool
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"""
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tasks = self.create_parallel_tasks()
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instructions = [
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"# Parallel Repository Indexing Execution Plan",
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"",
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"## Objective",
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f"Create comprehensive repository index for: {self.repo_path}",
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"",
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"## Execution Strategy",
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"",
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"Execute the following 5 tasks IN PARALLEL using Task tool.",
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"IMPORTANT: All 5 Task tool calls must be in a SINGLE message for parallel execution.",
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"",
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"## Tasks to Execute (Parallel)",
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""
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]
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for i, task in enumerate(tasks, 1):
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instructions.extend([
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f"### Task {i}: {task.description}",
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f"- Agent: {task.agent_type}",
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f"- ID: {task.task_id}",
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"",
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"**Prompt**:",
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"```",
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task.prompt,
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"```",
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""
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])
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instructions.extend([
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"## Expected Output",
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"",
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"Each task will return JSON with analysis results.",
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"After all tasks complete, merge the results into a single repository index.",
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"",
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"## Performance Expectations",
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"",
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"- Sequential execution: ~300ms",
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"- Parallel execution: ~60-100ms (3-5x faster)",
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"- No GIL limitations (API-level parallelism)",
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""
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])
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return "\n".join(instructions)
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def save_execution_plan(self, output_path: Path):
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"""Save execution plan to file"""
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instructions = self.generate_execution_instructions()
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output_path.write_text(instructions)
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print(f"📝 Execution plan saved to: {output_path}")
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def generate_task_tool_calls_code() -> str:
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"""
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Generate Python code showing how to make parallel Task tool calls
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This is example code for Claude Code to execute
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"""
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code = '''
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# Example: How to execute parallel tasks using Task tool
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# This should be executed by Claude Code, not by Python directly
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from pathlib import Path
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repo_path = Path(".")
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# Define 5 parallel tasks
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tasks = [
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# Task 1: Code Structure
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{
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"subagent_type": "Explore",
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"description": "Analyze code structure",
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"prompt": """Analyze code in superclaude/, setup/ directories.
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Use Glob to find all .py files.
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Output: JSON with directory structure."""
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},
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# Task 2: Documentation
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{
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"subagent_type": "Explore",
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"description": "Analyze documentation",
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"prompt": """Analyze docs/ and root .md files.
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Use Glob to find all .md files.
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Output: JSON with documentation structure."""
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},
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# Task 3: Configuration
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{
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"subagent_type": "Explore",
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"description": "Analyze configuration",
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"prompt": """Find all .toml, .yaml, .json config files.
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Output: JSON with config file list."""
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},
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# Task 4: Tests
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{
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"subagent_type": "Explore",
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"description": "Analyze tests",
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"prompt": """Analyze tests/ directory.
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Output: JSON with test structure."""
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},
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# Task 5: Scripts
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{
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"subagent_type": "Explore",
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"description": "Analyze scripts",
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"prompt": """Analyze scripts/, bin/ directories.
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Output: JSON with script list."""
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},
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]
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# CRITICAL: Execute all 5 Task tool calls in SINGLE message
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# This enables true parallel execution at Claude Code level
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# Pseudo-code for Claude Code execution:
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for task in tasks:
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Task(
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subagent_type=task["subagent_type"],
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description=task["description"],
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prompt=task["prompt"]
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)
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# All Task calls in same message = parallel execution
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# Results will come back as each task completes
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# Merge results into final repository index
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'''
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return code
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if __name__ == "__main__":
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"""Generate execution plan for Task tool parallel indexing"""
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repo_path = Path(".")
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indexer = TaskParallelIndexer(repo_path)
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# Save execution plan
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plan_path = repo_path / "PARALLEL_INDEXING_PLAN.md"
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indexer.save_execution_plan(plan_path)
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print("\n" + "="*80)
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print("✅ Task Tool Parallel Indexing Plan Generated")
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print("="*80)
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print(f"\nExecution plan: {plan_path}")
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print("\nNext steps:")
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print("1. Read the execution plan")
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print("2. Execute all 5 Task tool calls in SINGLE message")
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print("3. Wait for parallel execution to complete")
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print("4. Merge results into PROJECT_INDEX.md")
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print("\nExpected speedup: 3-5x faster than sequential")
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print("="*80 + "\n")
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