SuperClaude/PARALLEL_INDEXING_PLAN.md

Parallel Repository Indexing Execution Plan

Objective

Create comprehensive repository index for: /Users/kazuki/github/SuperClaude_Framework

Execution Strategy

Execute the following 5 tasks IN PARALLEL using Task tool. IMPORTANT: All 5 Task tool calls must be in a SINGLE message for parallel execution.

Tasks to Execute (Parallel)

Task 1: Analyze code structure

• Agent: Explore
• ID: code_structure

Prompt:

Analyze the code structure of this repository: /Users/kazuki/github/SuperClaude_Framework

Task: Find and analyze all source code directories (src/, lib/, superclaude/, setup/, apps/, packages/)

For each directory found:
1. List all Python/JavaScript/TypeScript files
2. Identify the purpose/responsibility
3. Note key files and entry points
4. Detect any organizational issues

Output format (JSON):
{
    "directories": [
        {
            "path": "relative/path",
            "purpose": "description",
            "file_count": 10,
            "key_files": ["file1.py", "file2.py"],
            "issues": ["redundant nesting", "orphaned files"]
        }
    ],
    "total_files": 100
}

Use Glob and Grep tools to search efficiently.
Be thorough: "very thorough" level.

Task 2: Analyze documentation

• Agent: Explore
• ID: documentation

Prompt:

Analyze the documentation of this repository: /Users/kazuki/github/SuperClaude_Framework

Task: Find and analyze all documentation (docs/, README*, *.md files)

For each documentation section:
1. List all markdown/rst files
2. Assess documentation coverage
3. Identify missing documentation
4. Detect redundant/duplicate docs

Output format (JSON):
{
    "directories": [
        {
            "path": "docs/",
            "purpose": "User/developer documentation",
            "file_count": 50,
            "coverage": "good|partial|poor",
            "missing": ["API reference", "Architecture guide"],
            "duplicates": ["README vs docs/README"]
        }
    ],
    "root_docs": ["README.md", "CLAUDE.md"],
    "total_files": 75
}

Use Glob to find all .md files.
Check for duplicate content patterns.

Task 3: Analyze configuration files

• Agent: Explore
• ID: configuration

Prompt:

Analyze the configuration files of this repository: /Users/kazuki/github/SuperClaude_Framework

Task: Find and analyze all configuration files (.toml, .yaml, .yml, .json, .ini, .cfg)

For each config file:
1. Identify purpose (build, deps, CI/CD, etc.)
2. Note importance level
3. Check for issues (deprecated, unused)

Output format (JSON):
{
    "config_files": [
        {
            "path": "pyproject.toml",
            "type": "python_project",
            "importance": "critical",
            "issues": []
        }
    ],
    "total_files": 15
}

Use Glob with appropriate patterns.

Task 4: Analyze test structure

• Agent: Explore
• ID: tests

Prompt:

Analyze the test structure of this repository: /Users/kazuki/github/SuperClaude_Framework

Task: Find and analyze all tests (tests/, __tests__/, *.test.*, *.spec.*)

For each test directory/file:
1. Count test files
2. Identify test types (unit, integration, performance)
3. Assess coverage (if pytest/coverage data available)

Output format (JSON):
{
    "test_directories": [
        {
            "path": "tests/",
            "test_count": 20,
            "types": ["unit", "integration", "benchmark"],
            "coverage": "unknown"
        }
    ],
    "total_tests": 25
}

Use Glob to find test files.

Task 5: Analyze scripts and utilities

• Agent: Explore
• ID: scripts

Prompt:

Analyze the scripts and utilities of this repository: /Users/kazuki/github/SuperClaude_Framework

Task: Find and analyze all scripts (scripts/, bin/, tools/, *.sh, *.bash)

For each script:
1. Identify purpose
2. Note language (bash, python, etc.)
3. Check if documented

Output format (JSON):
{
    "script_directories": [
        {
            "path": "scripts/",
            "script_count": 5,
            "purposes": ["build", "deploy", "utility"],
            "documented": true
        }
    ],
    "total_scripts": 10
}

Use Glob to find script files.

Expected Output

Each task will return JSON with analysis results. After all tasks complete, merge the results into a single repository index.

Performance Expectations

• Sequential execution: ~300ms
• Parallel execution: ~60-100ms (3-5x faster)
• No GIL limitations (API-level parallelism)