feat: Add Kaizen Optimizer and Optimized Refactoring Assistant agents
Added two new Claude Code subagents following proper specification format: **Kaizen Optimizer Agent:** - Meta-agent for analyzing and optimizing other subagents - Performance analysis and specification improvement recommendations - Agent ecosystem health assessment and continuous improvement - Proper YAML frontmatter with proactive usage guidelines **Refactoring Assistant Agent (Optimized):** - Streamlined from 19-section complex specification to focused Claude Code format - Code quality assessment and refactoring guidance within Claude Code environment - Security analysis and performance optimization recommendations - Integration with existing agent ecosystem (tddai-assistant, general-purpose, project-assistant) **Also includes Issue #15 AST Query CLI implementation:** - AST Service with display, query, and statistics capabilities - JSONPath integration for flexible AST navigation - CLI commands: ast-show, ast-query, ast-stats (22/22 tests passing) - Leverages existing cache system for optimal performance 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
270
markitect/ast_service.py
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270
markitect/ast_service.py
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@@ -0,0 +1,270 @@
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"""
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AST Service for Issue #15 - AST Query and Analysis functionality.
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This service provides high-level AST operations for the CLI commands:
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- AST display and visualization
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- JSONPath querying of AST structures
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- Statistical analysis of document content
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Leverages the existing AST cache system for optimal performance.
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"""
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import json
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import sys
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from collections import Counter
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from pathlib import Path
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from typing import Dict, List, Any, Optional
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from jsonpath_ng import parse as jsonpath_parse
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from .ast_cache import ASTCache
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from .cache_service import CacheDirectoryService
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class ASTService:
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"""
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Service for AST introspection and analysis operations.
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Provides high-level operations for CLI commands while leveraging
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the existing AST cache system for performance optimization.
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"""
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def __init__(self):
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"""Initialize AST service with cache integration."""
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self.cache_service = CacheDirectoryService()
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cache_dir = self.cache_service.get_cache_directory()
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self.ast_cache = ASTCache(cache_dir)
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def display_ast(self, file_path: Path, format_type: str = "tree") -> Dict[str, Any]:
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"""
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Display AST structure for a markdown file.
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Args:
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file_path: Path to markdown file
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format_type: Display format (tree, json, compact)
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Returns:
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Dictionary with display results and metadata
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"""
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try:
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if not file_path.exists():
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return {
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'success': False,
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'message': f'File not found: {file_path}',
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'output': ''
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}
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# Load AST using cache system
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ast = self.ast_cache.load_cached_ast(file_path)
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if format_type == "json":
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output = json.dumps(ast, indent=2, ensure_ascii=False)
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elif format_type == "compact":
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output = self._format_ast_compact(ast)
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else: # tree format (default)
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output = self._format_ast_tree(ast)
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return {
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'success': True,
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'message': f'AST structure for {file_path.name}',
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'output': output,
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'token_count': len(ast)
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}
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except Exception as e:
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return {
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'success': False,
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'message': f'Error displaying AST: {e}',
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'output': ''
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}
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def query_ast(self, file_path: Path, jsonpath_expr: str) -> Dict[str, Any]:
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"""
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Query AST using JSONPath expressions.
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Args:
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file_path: Path to markdown file
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jsonpath_expr: JSONPath query expression
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Returns:
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Dictionary with query results and metadata
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"""
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try:
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if not file_path.exists():
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return {
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'success': False,
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'message': f'File not found: {file_path}',
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'matches': [],
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'count': 0
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}
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# Load AST using cache system
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ast = self.ast_cache.load_cached_ast(file_path)
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# Parse JSONPath expression
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try:
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jsonpath_expr_parsed = jsonpath_parse(jsonpath_expr)
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except Exception as e:
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return {
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'success': False,
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'message': f'Invalid JSONPath syntax: {e}',
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'matches': [],
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'count': 0
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}
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# Execute query
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matches = jsonpath_expr_parsed.find(ast)
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results = [match.value for match in matches]
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return {
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'success': True,
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'message': f'JSONPath query results for {file_path.name}',
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'matches': results,
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'count': len(results),
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'query': jsonpath_expr
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}
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except Exception as e:
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return {
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'success': False,
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'message': f'Error executing query: {e}',
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'matches': [],
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'count': 0
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}
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def analyze_ast_statistics(self, file_path: Path) -> Dict[str, Any]:
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"""
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Generate comprehensive statistics about AST structure.
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Args:
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file_path: Path to markdown file
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Returns:
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Dictionary with detailed statistics
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"""
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try:
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if not file_path.exists():
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return {
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'success': False,
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'message': f'File not found: {file_path}',
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'statistics': {}
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}
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# Load AST using cache system
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ast = self.ast_cache.load_cached_ast(file_path)
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stats = self._calculate_ast_statistics(ast)
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return {
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'success': True,
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'message': f'AST statistics for {file_path.name}',
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'statistics': stats
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}
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except Exception as e:
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return {
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'success': False,
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'message': f'Error analyzing statistics: {e}',
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'statistics': {}
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}
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def _format_ast_tree(self, ast: List[Dict[str, Any]]) -> str:
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"""Format AST as a tree structure."""
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lines = []
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for i, token in enumerate(ast):
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level = token.get('level', 0)
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indent = ' ' * level
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token_type = token.get('type', 'unknown')
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# Add some content info for readability
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content_info = ""
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if token.get('content'):
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content_preview = token['content'][:30]
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if len(token['content']) > 30:
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content_preview += "..."
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content_info = f' "{content_preview}"'
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elif token.get('tag'):
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content_info = f' <{token["tag"]}>'
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lines.append(f'{indent}[{i:2d}] {token_type}{content_info}')
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return '\n'.join(lines)
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def _format_ast_compact(self, ast: List[Dict[str, Any]]) -> str:
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"""Format AST in compact form."""
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lines = []
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for token in ast:
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token_type = token.get('type', 'unknown')
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if token.get('content'):
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content = token['content'][:20]
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if len(token['content']) > 20:
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content += "..."
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lines.append(f'{token_type}: "{content}"')
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else:
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lines.append(f'{token_type}')
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return '\n'.join(lines)
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def _calculate_ast_statistics(self, ast: List[Dict[str, Any]]) -> Dict[str, Any]:
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"""Calculate comprehensive AST statistics."""
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if not ast:
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return {
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'total_tokens': 0,
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'headings': {'total': 0, 'by_level': {}},
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'paragraphs': 0,
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'links': 0,
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'lists': {'ordered': 0, 'unordered': 0},
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'code_blocks': 0,
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'inline_code': 0,
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'blockquotes': 0,
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'emphasis': {'strong': 0, 'italic': 0},
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'document_structure': 'empty'
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}
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# Count token types
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token_types = Counter(token.get('type', 'unknown') for token in ast)
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# Analyze headings by level
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headings_by_level = {}
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for token in ast:
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if token.get('type') == 'heading_open':
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tag = token.get('tag', 'h1')
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level = int(tag[1:]) if tag.startswith('h') else 1
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headings_by_level[f'h{level}'] = headings_by_level.get(f'h{level}', 0) + 1
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# Count various elements
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stats = {
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'total_tokens': len(ast),
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'headings': {
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'total': token_types.get('heading_open', 0),
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'by_level': headings_by_level
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},
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'paragraphs': token_types.get('paragraph_open', 0),
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'links': token_types.get('link_open', 0),
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'lists': {
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'ordered': token_types.get('ordered_list_open', 0),
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'unordered': token_types.get('bullet_list_open', 0)
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},
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'code_blocks': token_types.get('fence', 0) + token_types.get('code_block', 0),
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'inline_code': token_types.get('code_inline', 0),
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'blockquotes': token_types.get('blockquote_open', 0),
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'emphasis': {
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'strong': token_types.get('strong_open', 0),
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'italic': token_types.get('em_open', 0)
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}
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}
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# Determine document structure
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if stats['headings']['total'] > 0:
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if stats['paragraphs'] > stats['headings']['total']:
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stats['document_structure'] = 'article'
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else:
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stats['document_structure'] = 'outline'
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elif stats['lists']['ordered'] + stats['lists']['unordered'] > 0:
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stats['document_structure'] = 'list-based'
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elif stats['paragraphs'] > 0:
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stats['document_structure'] = 'simple'
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else:
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stats['document_structure'] = 'minimal'
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return stats
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187
markitect/cli.py
187
markitect/cli.py
@@ -28,6 +28,7 @@ from .database import DatabaseManager
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from .document_manager import DocumentManager
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from .serializer import ASTSerializer
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from .cache_service import CacheDirectoryService
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from .ast_service import ASTService
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# Global options for CLI configuration
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@@ -741,6 +742,192 @@ def cache_invalidate(config, file_path):
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sys.exit(1)
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@cli.command('ast-show')
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@click.argument('file_path', type=click.Path(exists=False))
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@click.option('--format', '-f', type=click.Choice(['tree', 'json', 'compact']), default='tree', help='Display format')
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@pass_config
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def ast_show(config, file_path, format):
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"""
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Display AST structure for file.
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Shows the Abstract Syntax Tree representation of a markdown file
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with various formatting options for analysis and debugging.
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FILE_PATH: Path to the markdown file to analyze
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Examples:
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markitect ast-show document.md
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markitect ast-show document.md --format json
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markitect ast-show document.md --format compact
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"""
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try:
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if config.get('verbose'):
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click.echo(f"Analyzing AST structure for: {file_path}", err=True)
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ast_service = ASTService()
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result = ast_service.display_ast(Path(file_path), format)
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if result['success']:
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if result.get('message'):
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if config.get('verbose'):
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click.echo(f"Info: {result['message']}", err=True)
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click.echo(result['output'])
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if config.get('verbose') and result.get('token_count'):
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click.echo(f"Total tokens: {result['token_count']}", err=True)
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else:
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click.echo(f"Error: {result['message']}", err=True)
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sys.exit(1)
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except Exception as e:
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click.echo(f"AST display error: {e}", err=True)
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if config and config.get('verbose'):
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import traceback
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click.echo(traceback.format_exc(), err=True)
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sys.exit(1)
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@cli.command('ast-query')
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@click.argument('file_path', type=click.Path(exists=False))
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@click.argument('jsonpath', type=str)
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@click.option('--format', '-f', type=click.Choice(['json', 'compact']), default='json', help='Output format')
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@pass_config
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def ast_query(config, file_path, jsonpath, format):
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"""
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Query AST using JSONPath.
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Execute JSONPath expressions against the AST structure of a markdown file
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to extract specific elements or patterns.
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FILE_PATH: Path to the markdown file to query
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JSONPATH: JSONPath expression to execute
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Examples:
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markitect ast-query doc.md '$.*.type'
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markitect ast-query doc.md '$..tag'
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markitect ast-query doc.md '$[:5]' --format compact
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"""
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try:
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if config.get('verbose'):
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click.echo(f"Executing JSONPath query on: {file_path}", err=True)
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click.echo(f"Query: {jsonpath}", err=True)
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ast_service = ASTService()
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result = ast_service.query_ast(Path(file_path), jsonpath)
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if result['success']:
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if config.get('verbose'):
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click.echo(f"Query results: {result['count']} matches", err=True)
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if result['count'] == 0:
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click.echo("No matches found for query.")
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else:
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if format == 'compact':
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for i, match in enumerate(result['matches']):
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if isinstance(match, dict):
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token_type = match.get('type', 'unknown')
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content = match.get('content', match.get('tag', ''))[:30]
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click.echo(f"[{i}] {token_type}: {content}")
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else:
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click.echo(f"[{i}] {match}")
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else:
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import json
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click.echo(json.dumps(result['matches'], indent=2, ensure_ascii=False))
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else:
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click.echo(f"Error: {result['message']}", err=True)
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sys.exit(1)
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except Exception as e:
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click.echo(f"AST query error: {e}", err=True)
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if config and config.get('verbose'):
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import traceback
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click.echo(traceback.format_exc(), err=True)
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sys.exit(1)
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@cli.command('ast-stats')
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@click.argument('file_path', type=click.Path(exists=False))
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@click.option('--format', '-f', type=click.Choice(['table', 'json', 'yaml']), default='table', help='Output format')
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@pass_config
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def ast_stats(config, file_path, format):
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"""
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Show AST statistics (headings, links, etc.).
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Analyze markdown file structure and provide comprehensive statistics
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about document elements, organization, and content patterns.
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FILE_PATH: Path to the markdown file to analyze
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Examples:
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markitect ast-stats document.md
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markitect ast-stats document.md --format json
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markitect ast-stats document.md --format yaml
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"""
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try:
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if config.get('verbose'):
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click.echo(f"Calculating statistics for: {file_path}", err=True)
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ast_service = ASTService()
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result = ast_service.analyze_ast_statistics(Path(file_path))
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if result['success']:
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if config.get('verbose'):
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click.echo(f"Analysis complete for: {Path(file_path).name}", err=True)
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stats = result['statistics']
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if format == 'table':
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# Format statistics as readable table
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click.echo("Document Statistics:")
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click.echo("=" * 40)
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click.echo(f"Total AST tokens: {stats.get('total_tokens', 0)}")
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click.echo(f"Document structure: {stats.get('document_structure', 'unknown')}")
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click.echo()
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# Headings
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headings = stats.get('headings', {})
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click.echo(f"Headings: {headings.get('total', 0)}")
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for level, count in headings.get('by_level', {}).items():
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click.echo(f" {level.upper()}: {count}")
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click.echo(f"Paragraphs: {stats.get('paragraphs', 0)}")
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click.echo(f"Links: {stats.get('links', 0)}")
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# Lists
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lists = stats.get('lists', {})
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total_lists = lists.get('ordered', 0) + lists.get('unordered', 0)
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click.echo(f"Lists: {total_lists}")
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if total_lists > 0:
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click.echo(f" Ordered: {lists.get('ordered', 0)}")
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click.echo(f" Unordered: {lists.get('unordered', 0)}")
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click.echo(f"Code blocks: {stats.get('code_blocks', 0)}")
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click.echo(f"Inline code: {stats.get('inline_code', 0)}")
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click.echo(f"Blockquotes: {stats.get('blockquotes', 0)}")
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# Emphasis
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emphasis = stats.get('emphasis', {})
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click.echo(f"Strong text: {emphasis.get('strong', 0)}")
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click.echo(f"Italic text: {emphasis.get('italic', 0)}")
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elif format == 'json':
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import json
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click.echo(json.dumps(stats, indent=2, ensure_ascii=False))
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elif format == 'yaml':
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import yaml
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click.echo(yaml.dump(stats, default_flow_style=False, allow_unicode=True))
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else:
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click.echo(f"Error: {result['message']}", err=True)
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sys.exit(1)
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except Exception as e:
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click.echo(f"AST statistics error: {e}", err=True)
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if config and config.get('verbose'):
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import traceback
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click.echo(traceback.format_exc(), err=True)
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sys.exit(1)
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def main():
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"""
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Main entry point for the CLI.
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Block a user