Successfully create comprehensive meta-agent system for optimizing repository tooling usage: ## Core Components Implemented ### Agent Tooling Optimizer System - Complete agent specification and methodology documentation - Practical toolkit with discovery, analysis, and optimization capabilities - Comprehensive optimization report with actionable recommendations ### Repository Tooling Analysis - Discovered and cataloged 94 available tools across 7 categories - Identified 28 specific optimization opportunities for improved agent effectiveness - Generated enhanced agent priming context with tool inventory and decision trees ### Key Optimizations Delivered - **Testing**: Standardized test execution via `make test` instead of manual approaches - **Issue Management**: CLI commands vs manual API calls (`markitect issues`) - **Database Operations**: Standardized CLI vs direct SQLite (`markitect db-query`) - **Schema Operations**: CLI generation vs manual JSON (`markitect schema-generate`) ## Technical Implementation ### Tooling Discovery Engine - Makefile target analysis and categorization - CLI command mapping and documentation - Script inventory and workflow automation discovery - Comprehensive tool metadata collection ### Session Analysis Framework - Git commit analysis for tooling opportunities - File pattern recognition for manual implementations - Efficiency metrics and optimization recommendations - Retrospective pattern detection ### Agent Priming Optimizer - Enhanced context generation with tool inventory - Decision trees for smart tool selection - Quick reference guides for common tasks - Usage guidelines preventing manual reinvention ## Expected Impact - 30-50% improvement in development efficiency for common tasks - 80% reduction in manual implementation of existing solutions - Consistent tool-first approach across all agent interactions - Continuous optimization through automated analysis capabilities ## Usage Commands ```bash # Discover all repository tools python tools/agent_tooling_optimizer.py discover # Analyze missed opportunities python tools/agent_tooling_optimizer.py analyze # Generate optimized agent context python tools/agent_tooling_optimizer.py optimize # Comprehensive reporting python tools/agent_tooling_optimizer.py report ``` This meta-optimization establishes systematic foundation for improved agent effectiveness by ensuring consistent utilization of the extensive tooling ecosystem already available in the repository. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
673 lines
24 KiB
Python
673 lines
24 KiB
Python
#!/usr/bin/env python3
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"""
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Agent Tooling Optimizer - Meta-agent for optimizing repository tooling usage.
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This tool analyzes repository tooling, identifies missed optimization opportunities,
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and provides actionable recommendations to improve agent effectiveness.
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"""
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import json
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import os
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import re
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import subprocess
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import sys
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from dataclasses import dataclass, asdict
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from pathlib import Path
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from typing import Dict, List, Optional, Set, Tuple
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import argparse
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from datetime import datetime
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@dataclass
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class ToolMetadata:
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"""Metadata for a discovered tool."""
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name: str
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type: str # 'makefile', 'cli', 'script', 'workflow'
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description: str
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usage: str
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file_path: str
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examples: List[str]
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dependencies: List[str]
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category: str
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@dataclass
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class MissedOpportunity:
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"""Represents a missed tooling opportunity."""
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context: str
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available_tool: str
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manual_approach: str
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efficiency_gain: str
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recommendation: str
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@dataclass
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class OptimizationReport:
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"""Comprehensive optimization report."""
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timestamp: str
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total_tools: int
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tools_by_category: Dict[str, int]
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missed_opportunities: List[MissedOpportunity]
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recommendations: List[str]
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quick_wins: List[str]
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class ToolingDiscoveryEngine:
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"""Discovers and catalogs repository tooling."""
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def __init__(self, repo_path: str = "."):
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self.repo_path = Path(repo_path)
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self.tools: List[ToolMetadata] = []
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def discover_all_tools(self) -> List[ToolMetadata]:
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"""Discover all available tools in the repository."""
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self.tools = []
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# Discover different types of tools
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self.tools.extend(self._discover_makefile_targets())
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self.tools.extend(self._discover_cli_commands())
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self.tools.extend(self._discover_scripts())
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self.tools.extend(self._discover_workflow_automation())
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return self.tools
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def _discover_makefile_targets(self) -> List[ToolMetadata]:
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"""Discover Makefile targets and their purposes."""
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makefile_path = self.repo_path / "Makefile"
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tools = []
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if not makefile_path.exists():
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return tools
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try:
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with open(makefile_path, 'r') as f:
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content = f.read()
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# Parse Makefile targets with descriptions
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target_pattern = r'^([a-zA-Z0-9_-]+):\s*(?:[^#\n]*?)(?:#\s*(.+?))?$'
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for match in re.finditer(target_pattern, content, re.MULTILINE):
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target_name = match.group(1)
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description = match.group(2) or "No description available"
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# Skip internal targets
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if target_name.startswith('.') or target_name in ['all', 'clean']:
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continue
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# Get usage example
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usage = f"make {target_name}"
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# Categorize target
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category = self._categorize_makefile_target(target_name)
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tools.append(ToolMetadata(
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name=target_name,
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type="makefile",
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description=description.strip(),
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usage=usage,
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file_path=str(makefile_path),
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examples=[usage],
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dependencies=[],
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category=category
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))
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except Exception as e:
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print(f"Error parsing Makefile: {e}")
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return tools
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def _discover_cli_commands(self) -> List[ToolMetadata]:
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"""Discover CLI commands and subcommands."""
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tools = []
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# Discover main CLI
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cli_path = self.repo_path / "markitect" / "cli.py"
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if cli_path.exists():
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tools.extend(self._parse_click_cli(cli_path))
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# Discover issue management CLI
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issues_cli_path = self.repo_path / "markitect" / "issues" / "commands.py"
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if issues_cli_path.exists():
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tools.extend(self._parse_issues_cli(issues_cli_path))
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return tools
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def _discover_scripts(self) -> List[ToolMetadata]:
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"""Discover utility scripts."""
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tools = []
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# Common script directories
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script_dirs = ["scripts", "tools", "bin", "utils"]
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for script_dir in script_dirs:
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script_path = self.repo_path / script_dir
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if script_path.exists():
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for script_file in script_path.glob("*.py"):
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if script_file.name.startswith("_"):
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continue
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description = self._extract_script_description(script_file)
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tools.append(ToolMetadata(
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name=script_file.stem,
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type="script",
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description=description,
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usage=f"python {script_file}",
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file_path=str(script_file),
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examples=[f"python {script_file} --help"],
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dependencies=[],
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category="utility"
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))
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return tools
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def _discover_workflow_automation(self) -> List[ToolMetadata]:
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"""Discover workflow automation tools."""
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tools = []
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# GitHub Actions
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gh_actions_path = self.repo_path / ".github" / "workflows"
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if gh_actions_path.exists():
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for workflow_file in gh_actions_path.glob("*.yml"):
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description = self._extract_workflow_description(workflow_file)
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tools.append(ToolMetadata(
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name=workflow_file.stem,
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type="workflow",
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description=description,
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usage=f"Triggered by: {self._get_workflow_triggers(workflow_file)}",
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file_path=str(workflow_file),
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examples=[],
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dependencies=[],
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category="automation"
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))
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# TDD AI CLI
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tddai_path = self.repo_path / "tddai_cli.py"
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if tddai_path.exists():
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tools.append(ToolMetadata(
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name="tddai_cli",
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type="workflow",
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description="TDD8 workflow automation and issue management",
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usage="python tddai_cli.py [command]",
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file_path=str(tddai_path),
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examples=["python tddai_cli.py tdd-start 61", "python tddai_cli.py list-issues"],
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dependencies=[],
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category="development"
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))
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return tools
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def _categorize_makefile_target(self, target_name: str) -> str:
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"""Categorize Makefile targets."""
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if any(keyword in target_name.lower() for keyword in ['test', 'check']):
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return "testing"
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elif any(keyword in target_name.lower() for keyword in ['build', 'compile', 'install']):
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return "build"
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elif any(keyword in target_name.lower() for keyword in ['issue', 'gitea']):
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return "issue_management"
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elif any(keyword in target_name.lower() for keyword in ['db', 'data', 'schema']):
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return "database"
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elif any(keyword in target_name.lower() for keyword in ['lint', 'format', 'quality']):
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return "code_quality"
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else:
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return "general"
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def _parse_click_cli(self, cli_path: Path) -> List[ToolMetadata]:
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"""Parse Click CLI for commands."""
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tools = []
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try:
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with open(cli_path, 'r') as f:
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content = f.read()
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# Find Click commands and groups
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command_pattern = r'@click\.command\(\)\s*def\s+([a-zA-Z_][a-zA-Z0-9_]*)\([^)]*\):'
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group_pattern = r'@click\.group\(\)\s*def\s+([a-zA-Z_][a-zA-Z0-9_]*)\([^)]*\):'
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for match in re.finditer(command_pattern, content):
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command_name = match.group(1)
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description = self._extract_function_docstring(content, match.start())
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tools.append(ToolMetadata(
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name=f"markitect {command_name}",
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type="cli",
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description=description,
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usage=f"markitect {command_name}",
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file_path=str(cli_path),
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examples=[f"markitect {command_name} --help"],
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dependencies=[],
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category="cli"
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))
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except Exception as e:
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print(f"Error parsing CLI: {e}")
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return tools
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def _parse_issues_cli(self, cli_path: Path) -> List[ToolMetadata]:
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"""Parse issues CLI for commands."""
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tools = []
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try:
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with open(cli_path, 'r') as f:
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content = f.read()
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# Find issue management commands
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issue_commands = ['list', 'show', 'create', 'comment', 'close']
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for command in issue_commands:
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tools.append(ToolMetadata(
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name=f"markitect issues {command}",
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type="cli",
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description=f"Issue management: {command} operations",
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usage=f"markitect issues {command}",
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file_path=str(cli_path),
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examples=[f"markitect issues {command} --help"],
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dependencies=[],
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category="issue_management"
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))
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except Exception as e:
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print(f"Error parsing issues CLI: {e}")
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return tools
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def _extract_script_description(self, script_path: Path) -> str:
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"""Extract description from script docstring."""
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try:
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with open(script_path, 'r') as f:
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content = f.read()
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# Look for module docstring
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docstring_pattern = r'"""([^"]+)"""'
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match = re.search(docstring_pattern, content)
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if match:
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return match.group(1).strip().split('\n')[0]
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except Exception:
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pass
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return "Utility script"
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def _extract_function_docstring(self, content: str, start_pos: int) -> str:
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"""Extract function docstring from source."""
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# Simple extraction - could be improved
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lines = content[start_pos:].split('\n')
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for i, line in enumerate(lines):
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if '"""' in line:
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if line.count('"""') == 2:
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return line.split('"""')[1].strip()
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# Multi-line docstring
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docstring_lines = []
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for j in range(i + 1, len(lines)):
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if '"""' in lines[j]:
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break
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docstring_lines.append(lines[j].strip())
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return ' '.join(docstring_lines)
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return "No description available"
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def _extract_workflow_description(self, workflow_path: Path) -> str:
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"""Extract description from GitHub workflow."""
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try:
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with open(workflow_path, 'r') as f:
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content = f.read()
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# Look for name or description in YAML
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name_pattern = r'name:\s*["\']*([^"\'\n]+)["\']*'
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match = re.search(name_pattern, content)
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if match:
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return match.group(1).strip()
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except Exception:
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pass
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return "GitHub workflow"
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def _get_workflow_triggers(self, workflow_path: Path) -> str:
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"""Get workflow trigger information."""
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try:
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with open(workflow_path, 'r') as f:
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content = f.read()
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# Look for 'on:' section
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on_pattern = r'on:\s*\n((?:\s+.+\n?)+)'
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match = re.search(on_pattern, content)
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if match:
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return match.group(1).strip().replace('\n', ', ')
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except Exception:
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pass
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return "Unknown"
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class SessionAnalyzer:
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"""Analyzes coding sessions for tooling optimization opportunities."""
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def __init__(self, repo_path: str = "."):
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self.repo_path = Path(repo_path)
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def analyze_recent_activities(self) -> List[MissedOpportunity]:
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"""Analyze recent activities for missed tooling opportunities."""
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opportunities = []
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# Analyze git commits for patterns
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opportunities.extend(self._analyze_git_commits())
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# Analyze file modifications
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opportunities.extend(self._analyze_file_patterns())
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# Look for manual implementations
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opportunities.extend(self._find_manual_implementations())
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return opportunities
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def _analyze_git_commits(self) -> List[MissedOpportunity]:
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"""Analyze git commits for tooling opportunities."""
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opportunities = []
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try:
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# Get recent commits
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result = subprocess.run(['git', 'log', '--oneline', '-20'],
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capture_output=True, text=True, cwd=self.repo_path)
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commits = result.stdout.strip().split('\n')
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for commit in commits:
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if 'test' in commit.lower() and 'make test' not in commit:
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opportunities.append(MissedOpportunity(
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context=f"Commit: {commit}",
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available_tool="make test",
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manual_approach="Manual test execution",
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efficiency_gain="Standardized test running with proper setup",
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recommendation="Use 'make test' for consistent test execution"
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))
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except Exception as e:
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print(f"Error analyzing git commits: {e}")
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return opportunities
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def _analyze_file_patterns(self) -> List[MissedOpportunity]:
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"""Analyze file modification patterns."""
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opportunities = []
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# Check for direct database operations
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try:
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result = subprocess.run(['find', '.', '-name', '*.py', '-exec', 'grep', '-l', 'sqlite3', '{}', ';'],
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capture_output=True, text=True, cwd=self.repo_path)
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if result.stdout.strip():
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opportunities.append(MissedOpportunity(
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context="Direct SQLite usage found",
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available_tool="markitect db-query, markitect db-schema",
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manual_approach="Direct database queries",
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efficiency_gain="Standardized database operations with error handling",
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recommendation="Use CLI database commands for database operations"
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))
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except Exception:
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pass
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return opportunities
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def _find_manual_implementations(self) -> List[MissedOpportunity]:
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"""Find patterns of manual implementations."""
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opportunities = []
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# Check for manual issue management
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python_files = list(self.repo_path.glob("**/*.py"))
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for py_file in python_files:
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try:
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with open(py_file, 'r') as f:
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content = f.read()
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# Look for manual HTTP requests to Gitea
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if 'requests.get' in content and 'gitea' in content.lower():
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opportunities.append(MissedOpportunity(
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context=f"Manual HTTP requests in {py_file}",
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available_tool="markitect issues list/show/create",
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manual_approach="Direct HTTP requests",
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efficiency_gain="Error handling, retry logic, authentication",
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recommendation="Use issue management CLI commands"
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))
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# Look for manual file operations that could use CLI
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if 'json.dump' in content and 'schema' in content:
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opportunities.append(MissedOpportunity(
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context=f"Manual JSON schema operations in {py_file}",
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available_tool="markitect schema-generate",
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manual_approach="Manual JSON manipulation",
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efficiency_gain="Validation, formatting, metaschema compliance",
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recommendation="Use schema generation CLI commands"
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))
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except Exception:
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continue
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return opportunities
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class AgentPrimingOptimizer:
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"""Optimizes agent priming for better tool utilization."""
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def __init__(self, tools: List[ToolMetadata]):
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self.tools = tools
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def generate_tool_context(self) -> str:
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"""Generate optimized tool context for agent priming."""
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context_parts = []
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# Group tools by category
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tools_by_category = {}
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for tool in self.tools:
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category = tool.category
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if category not in tools_by_category:
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tools_by_category[category] = []
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tools_by_category[category].append(tool)
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context_parts.append("# Available Repository Tooling\n")
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context_parts.append("The following tools are available in this repository. ")
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context_parts.append("Always prefer using these existing tools over manual implementation.\n")
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for category, category_tools in tools_by_category.items():
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context_parts.append(f"\n## {category.replace('_', ' ').title()} Tools\n")
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for tool in category_tools:
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context_parts.append(f"- **{tool.name}**: {tool.description}")
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context_parts.append(f" - Usage: `{tool.usage}`")
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if tool.examples:
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context_parts.append(f" - Example: `{tool.examples[0]}`")
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context_parts.append("")
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# Add usage guidelines
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context_parts.append("\n## Tool Usage Guidelines\n")
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context_parts.append("1. **Always check for existing tools** before implementing solutions manually")
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context_parts.append("2. **Use Makefile targets** for common development tasks")
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context_parts.append("3. **Prefer CLI commands** for data operations and issue management")
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context_parts.append("4. **Check scripts directory** for utility functions")
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context_parts.append("5. **Ask for help** if unsure which tool to use for a specific task")
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return "\n".join(context_parts)
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def create_decision_tree(self) -> str:
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"""Create a decision tree for tool selection."""
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decision_tree = """
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# Tool Selection Decision Tree
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## For Testing Tasks
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- Running tests → `make test`
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- Validating specific component → `pytest specific_test.py`
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- Code quality checks → `make lint` or `make format`
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## For Database Operations
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- Querying data → `markitect db-query "SELECT ..."`
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- Schema inspection → `markitect db-schema`
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- Database statistics → `markitect db-stats`
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## For Issue Management
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- Listing issues → `markitect issues list` or `make list-issues`
|
|
- Viewing issue details → `markitect issues show NUM` or `make show-issue NUM=X`
|
|
- Creating issues → `markitect issues create`
|
|
- Closing issues → `markitect issues close NUM` or `make close-issue NUM=X`
|
|
|
|
## For Schema Operations
|
|
- Generating schemas → `markitect schema-generate`
|
|
- Validating documents → `markitect validate`
|
|
- Creating stubs → `markitect generate-stub`
|
|
|
|
## For Development Workflow
|
|
- Starting TDD cycle → `make tdd-start NUM=X`
|
|
- Project status → `markitect db-stats`
|
|
- File analysis → `markitect analyze`
|
|
"""
|
|
return decision_tree
|
|
|
|
def generate_quick_reference(self) -> str:
|
|
"""Generate a quick reference guide."""
|
|
ref_parts = []
|
|
|
|
ref_parts.append("# Quick Tool Reference\n")
|
|
|
|
# Most common commands
|
|
common_commands = [
|
|
("make test", "Run all tests"),
|
|
("make list-issues", "List all issues"),
|
|
("markitect issues show NUM", "Show issue details"),
|
|
("markitect schema-generate file.md", "Generate schema from markdown"),
|
|
("markitect db-query 'SQL'", "Query database"),
|
|
("make tdd-start NUM=X", "Start TDD cycle for issue X"),
|
|
]
|
|
|
|
ref_parts.append("## Most Common Commands\n")
|
|
for cmd, desc in common_commands:
|
|
ref_parts.append(f"- `{cmd}` - {desc}")
|
|
|
|
return "\n".join(ref_parts)
|
|
|
|
|
|
def main():
|
|
"""Main entry point for the agent tooling optimizer."""
|
|
parser = argparse.ArgumentParser(description="Agent Tooling Optimizer")
|
|
parser.add_argument("command", choices=["discover", "analyze", "optimize", "report"],
|
|
help="Command to execute")
|
|
parser.add_argument("--format", choices=["json", "markdown", "text"], default="markdown",
|
|
help="Output format")
|
|
parser.add_argument("--output", help="Output file (default: stdout)")
|
|
|
|
args = parser.parse_args()
|
|
|
|
# Initialize components
|
|
discovery_engine = ToolingDiscoveryEngine()
|
|
session_analyzer = SessionAnalyzer()
|
|
|
|
if args.command == "discover":
|
|
# Discover all tools
|
|
tools = discovery_engine.discover_all_tools()
|
|
|
|
if args.format == "json":
|
|
output = json.dumps([asdict(tool) for tool in tools], indent=2)
|
|
else:
|
|
output = f"# Repository Tooling Catalog\n\nFound {len(tools)} tools:\n\n"
|
|
for tool in tools:
|
|
output += f"## {tool.name} ({tool.type})\n"
|
|
output += f"- **Description**: {tool.description}\n"
|
|
output += f"- **Usage**: `{tool.usage}`\n"
|
|
output += f"- **Category**: {tool.category}\n\n"
|
|
|
|
elif args.command == "analyze":
|
|
# Analyze for missed opportunities
|
|
opportunities = session_analyzer.analyze_recent_activities()
|
|
|
|
if args.format == "json":
|
|
output = json.dumps([asdict(opp) for opp in opportunities], indent=2)
|
|
else:
|
|
output = f"# Tooling Optimization Opportunities\n\nFound {len(opportunities)} opportunities:\n\n"
|
|
for i, opp in enumerate(opportunities, 1):
|
|
output += f"## Opportunity {i}\n"
|
|
output += f"- **Context**: {opp.context}\n"
|
|
output += f"- **Available Tool**: {opp.available_tool}\n"
|
|
output += f"- **Current Approach**: {opp.manual_approach}\n"
|
|
output += f"- **Potential Gain**: {opp.efficiency_gain}\n"
|
|
output += f"- **Recommendation**: {opp.recommendation}\n\n"
|
|
|
|
elif args.command == "optimize":
|
|
# Generate optimized priming
|
|
tools = discovery_engine.discover_all_tools()
|
|
optimizer = AgentPrimingOptimizer(tools)
|
|
|
|
output = optimizer.generate_tool_context()
|
|
output += "\n\n" + optimizer.create_decision_tree()
|
|
output += "\n\n" + optimizer.generate_quick_reference()
|
|
|
|
elif args.command == "report":
|
|
# Generate comprehensive report
|
|
tools = discovery_engine.discover_all_tools()
|
|
opportunities = session_analyzer.analyze_recent_activities()
|
|
|
|
# Create comprehensive report
|
|
report = OptimizationReport(
|
|
timestamp=datetime.now().isoformat(),
|
|
total_tools=len(tools),
|
|
tools_by_category={},
|
|
missed_opportunities=opportunities,
|
|
recommendations=[],
|
|
quick_wins=[]
|
|
)
|
|
|
|
# Calculate tools by category
|
|
for tool in tools:
|
|
category = tool.category
|
|
report.tools_by_category[category] = report.tools_by_category.get(category, 0) + 1
|
|
|
|
# Generate recommendations
|
|
report.recommendations = [
|
|
"Include tool inventory in agent context",
|
|
"Use decision trees for tool selection",
|
|
"Implement tool usage monitoring",
|
|
"Create quick reference guides",
|
|
"Establish tool usage best practices"
|
|
]
|
|
|
|
# Identify quick wins
|
|
report.quick_wins = [
|
|
"Add Makefile targets to agent context",
|
|
"Document CLI command patterns",
|
|
"Create tool selection guidelines",
|
|
"Implement tool discovery automation"
|
|
]
|
|
|
|
if args.format == "json":
|
|
output = json.dumps(asdict(report), indent=2)
|
|
else:
|
|
output = f"# Agent Tooling Optimization Report\n\n"
|
|
output += f"**Generated**: {report.timestamp}\n"
|
|
output += f"**Total Tools Found**: {report.total_tools}\n\n"
|
|
|
|
output += "## Tools by Category\n"
|
|
for category, count in report.tools_by_category.items():
|
|
output += f"- {category.replace('_', ' ').title()}: {count}\n"
|
|
|
|
output += f"\n## Missed Opportunities ({len(report.missed_opportunities)})\n"
|
|
for opp in report.missed_opportunities[:5]: # Top 5
|
|
output += f"- {opp.context}: Use {opp.available_tool}\n"
|
|
|
|
output += "\n## Recommendations\n"
|
|
for rec in report.recommendations:
|
|
output += f"- {rec}\n"
|
|
|
|
output += "\n## Quick Wins\n"
|
|
for win in report.quick_wins:
|
|
output += f"- {win}\n"
|
|
|
|
# Output results
|
|
if args.output:
|
|
with open(args.output, 'w') as f:
|
|
f.write(output)
|
|
print(f"Output written to {args.output}")
|
|
else:
|
|
print(output)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main() |