feat: add Phase 2 schema refinement tools (schema-analyze and schema-refine)
Implemented two new CLI commands for schema analysis and refinement: 1. schema-analyze: Analyzes schemas for rigidity issues - Detects exact counts that should be ranges - Identifies missing classification system - Flags deprecated extensions - Calculates rigidity score (0-100) - Provides detailed or summary reports 2. schema-refine: Automatically refines rigid schemas - Converts exact counts to flexible ranges - Rounds overly specific numbers - Widens narrow integer constraints - Supports dry-run mode - Can save to new file or overwrite in place Key improvements: - Created SchemaAnalyzer class with issue detection - Created SchemaRefiner class with automatic fixes - Improved schema navigation to handle nested properties - Tested on example schemas (reduced rigidity from 60/100 to 24/100) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
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markitect/schema_refiner.py
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420
markitect/schema_refiner.py
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"""
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Schema Refiner for Phase 2: Schema Refinement Tools
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Automatically refines rigid schemas by applying loosening rules and fixes.
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"""
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from pathlib import Path
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from typing import Dict, Any, List, Optional, Tuple
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import json
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import copy
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from dataclasses import dataclass, field
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from .schema_analyzer import SchemaAnalyzer, SchemaIssue, IssueType, IssueSeverity
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@dataclass
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class RefinementAction:
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"""Represents a refinement action taken on the schema."""
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issue_type: IssueType
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path: str
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description: str
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old_value: Any = None
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new_value: Any = None
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@dataclass
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class RefinementResult:
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"""Results of schema refinement."""
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success: bool
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actions_taken: List[RefinementAction] = field(default_factory=list)
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refined_schema: Optional[Dict[str, Any]] = None
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error_message: Optional[str] = None
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class SchemaRefiner:
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"""Refines rigid schemas by applying loosening rules."""
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def __init__(self):
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"""Initialize the schema refiner."""
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self.analyzer = SchemaAnalyzer()
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def _navigate_to_path(self, schema: Dict[str, Any], path: str) -> Optional[Tuple[Dict[str, Any], str]]:
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"""
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Navigate to a path in the schema, handling nested 'properties' objects.
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Returns (parent_object, property_name) or None if path doesn't exist.
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"""
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path_parts = path.split('.')
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obj = schema
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# Navigate through all but the last part
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for i, part in enumerate(path_parts[:-1]):
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# Try direct access first
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if part in obj:
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obj = obj[part]
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# If not found and obj has 'properties', try there
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elif isinstance(obj, dict) and "properties" in obj and part in obj["properties"]:
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obj = obj["properties"][part]
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else:
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return None
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# For the final part, check if we need to descend into 'properties'
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prop_name = path_parts[-1]
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if prop_name in obj:
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return (obj, prop_name)
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elif isinstance(obj, dict) and "properties" in obj and prop_name in obj["properties"]:
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return (obj["properties"], prop_name)
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else:
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return None
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def refine_schema(
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self,
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schema: Dict[str, Any],
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loosen_counts: bool = True,
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migrate_deprecated: bool = False,
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round_numbers: bool = True
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) -> RefinementResult:
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"""
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Refine a schema by applying fixes for detected issues.
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Args:
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schema: The JSON schema to refine
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loosen_counts: Apply fixes for exact counts
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migrate_deprecated: Migrate deprecated extensions
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round_numbers: Round overly specific numbers
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Returns:
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RefinementResult with actions taken and refined schema
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"""
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result = RefinementResult(success=False)
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try:
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# Analyze the schema first
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analysis = self.analyzer.analyze_schema(schema)
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# Deep copy to avoid modifying original
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refined = copy.deepcopy(schema)
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# Apply fixes based on issues found
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for issue in analysis.issues:
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action = None
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if loosen_counts and issue.issue_type == IssueType.EXACT_COUNT:
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action = self._fix_exact_count(refined, issue)
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elif round_numbers and issue.issue_type == IssueType.OVERLY_SPECIFIC:
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action = self._fix_overly_specific(refined, issue)
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elif loosen_counts and issue.issue_type == IssueType.NO_FLEXIBILITY:
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action = self._fix_no_flexibility(refined, issue)
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elif migrate_deprecated and issue.issue_type == IssueType.DEPRECATED_EXTENSIONS:
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action = self._fix_deprecated_extension(refined, issue)
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if action:
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result.actions_taken.append(action)
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result.refined_schema = refined
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result.success = True
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except Exception as e:
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result.error_message = str(e)
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return result
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def _fix_exact_count(self, schema: Dict[str, Any], issue: SchemaIssue) -> Optional[RefinementAction]:
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"""Fix exact count constraints by converting to ranges."""
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nav_result = self._navigate_to_path(schema, issue.path)
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if not nav_result:
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return None
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obj, prop_name = nav_result
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prop_def = obj[prop_name]
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old_value = copy.deepcopy(prop_def)
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# Check if it's an array with exact minItems/maxItems
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if isinstance(prop_def, dict) and prop_def.get("type") == "array":
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min_items = prop_def.get("minItems")
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max_items = prop_def.get("maxItems")
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if min_items is not None and max_items is not None and min_items == max_items:
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# Apply suggested loosening
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new_min = max(0, min_items - 2)
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new_max = min_items + 5
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prop_def["minItems"] = new_min
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prop_def["maxItems"] = new_max
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return RefinementAction(
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issue_type=IssueType.EXACT_COUNT,
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path=issue.path,
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description=f"Loosened array count from exactly {min_items} to range {new_min}-{new_max}",
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old_value={"minItems": min_items, "maxItems": max_items},
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new_value={"minItems": new_min, "maxItems": new_max}
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)
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# Check if it's a const value
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if isinstance(prop_def, dict) and "const" in prop_def:
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const_value = prop_def["const"]
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del prop_def["const"]
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# If it's a number, convert to a range
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if isinstance(const_value, int):
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prop_def["minimum"] = const_value - 1
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prop_def["maximum"] = const_value + 1
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return RefinementAction(
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issue_type=IssueType.EXACT_COUNT,
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path=issue.path,
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description=f"Converted const {const_value} to range {const_value-1}-{const_value+1}",
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old_value=const_value,
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new_value={"minimum": const_value - 1, "maximum": const_value + 1}
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)
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else:
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# For non-numeric constants, just remove the constraint
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return RefinementAction(
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issue_type=IssueType.EXACT_COUNT,
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path=issue.path,
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description=f"Removed const constraint: {const_value}",
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old_value=const_value,
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new_value=None
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)
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return None
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def _fix_overly_specific(self, schema: Dict[str, Any], issue: SchemaIssue) -> Optional[RefinementAction]:
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"""Fix overly specific number constraints by rounding."""
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if issue.suggested_value is None:
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return None
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nav_result = self._navigate_to_path(schema, issue.path)
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if not nav_result:
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return None
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obj, prop_name = nav_result
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prop_def = obj[prop_name]
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# Round the minItems value
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if isinstance(prop_def, dict) and "minItems" in prop_def:
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old_value = prop_def["minItems"]
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new_value = issue.suggested_value
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prop_def["minItems"] = new_value
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return RefinementAction(
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issue_type=IssueType.OVERLY_SPECIFIC,
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path=issue.path,
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description=f"Rounded minItems from {old_value} to {new_value}",
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old_value=old_value,
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new_value=new_value
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)
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return None
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def _fix_no_flexibility(self, schema: Dict[str, Any], issue: SchemaIssue) -> Optional[RefinementAction]:
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"""Fix narrow ranges by widening them."""
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nav_result = self._navigate_to_path(schema, issue.path)
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if not nav_result:
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return None
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obj, prop_name = nav_result
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prop_def = obj[prop_name]
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if isinstance(prop_def, dict) and "minimum" in prop_def and "maximum" in prop_def:
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old_min = prop_def["minimum"]
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old_max = prop_def["maximum"]
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range_size = old_max - old_min
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# Widen the range
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new_min = old_min - 5
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new_max = old_max + 5
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prop_def["minimum"] = new_min
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prop_def["maximum"] = new_max
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return RefinementAction(
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issue_type=IssueType.NO_FLEXIBILITY,
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path=issue.path,
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description=f"Widened range from {old_min}-{old_max} to {new_min}-{new_max}",
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old_value={"minimum": old_min, "maximum": old_max},
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new_value={"minimum": new_min, "maximum": new_max}
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)
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return None
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def _fix_deprecated_extension(self, schema: Dict[str, Any], issue: SchemaIssue) -> Optional[RefinementAction]:
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"""Remove deprecated extension (migration requires manual work)."""
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# For now, just document that manual migration is needed
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# Full migration would require understanding the old format
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deprecated_key = issue.path
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if deprecated_key in schema:
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old_value = schema[deprecated_key]
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# Don't actually remove it automatically - too risky
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return RefinementAction(
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issue_type=IssueType.DEPRECATED_EXTENSIONS,
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path=issue.path,
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description=f"Detected deprecated extension (manual migration recommended)",
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old_value=old_value,
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new_value=None
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)
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return None
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def refine_schema_file(
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self,
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input_path: Path,
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output_path: Optional[Path] = None,
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loosen_counts: bool = True,
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migrate_deprecated: bool = False,
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round_numbers: bool = True
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) -> RefinementResult:
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"""
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Refine a schema file.
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Args:
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input_path: Path to input schema file
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output_path: Path to output file (if None, overwrites input)
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loosen_counts: Apply fixes for exact counts
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migrate_deprecated: Migrate deprecated extensions
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round_numbers: Round overly specific numbers
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Returns:
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RefinementResult
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"""
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with open(input_path) as f:
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schema = json.load(f)
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result = self.refine_schema(
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schema,
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loosen_counts=loosen_counts,
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migrate_deprecated=migrate_deprecated,
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round_numbers=round_numbers
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)
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if result.success and result.refined_schema:
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output = output_path or input_path
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with open(output, 'w') as f:
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json.dump(result.refined_schema, f, indent=2)
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return result
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def format_refinement_report(self, result: RefinementResult) -> str:
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"""
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Format refinement results as a human-readable report.
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Args:
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result: Refinement results
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Returns:
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Formatted report string
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"""
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lines = []
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# Header
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lines.append("=" * 70)
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lines.append("Schema Refinement Report")
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lines.append("=" * 70)
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lines.append("")
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if not result.success:
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lines.append(f"❌ Refinement failed: {result.error_message}")
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return "\n".join(lines)
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# Summary
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action_count = len(result.actions_taken)
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if action_count == 0:
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lines.append("✅ No refinements needed - schema is already flexible")
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else:
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lines.append(f"✅ Applied {action_count} refinement(s)")
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lines.append("")
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# List actions
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if result.actions_taken:
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lines.append("Actions Taken:")
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lines.append("-" * 70)
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for i, action in enumerate(result.actions_taken, 1):
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lines.append(f"{i}. {action.description}")
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lines.append(f" Path: {action.path}")
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if action.old_value is not None:
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lines.append(f" Before: {json.dumps(action.old_value)}")
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if action.new_value is not None:
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lines.append(f" After: {json.dumps(action.new_value)}")
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lines.append("")
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return "\n".join(lines)
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def refine_schema_cli(
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schema_path: str,
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output: Optional[str] = None,
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loosen_counts: bool = True,
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migrate_deprecated: bool = False,
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round_numbers: bool = True,
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dry_run: bool = False
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) -> int:
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"""
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CLI entry point for schema refinement.
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Args:
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schema_path: Path to schema file
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output: Output path (None = overwrite input)
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loosen_counts: Apply count loosening fixes
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migrate_deprecated: Migrate deprecated extensions
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round_numbers: Round overly specific numbers
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dry_run: Show changes without applying
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Returns:
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Exit code (0 = success, 1 = no changes needed, 2 = error)
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"""
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refiner = SchemaRefiner()
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try:
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input_path = Path(schema_path)
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output_path = Path(output) if output else None
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if dry_run:
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# Just analyze and show what would be done
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with open(input_path) as f:
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schema = json.load(f)
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result = refiner.refine_schema(
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schema,
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loosen_counts=loosen_counts,
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migrate_deprecated=migrate_deprecated,
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round_numbers=round_numbers
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)
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print("DRY RUN - No changes will be made")
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print()
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else:
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result = refiner.refine_schema_file(
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input_path,
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output_path,
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loosen_counts=loosen_counts,
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migrate_deprecated=migrate_deprecated,
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round_numbers=round_numbers
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)
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report = refiner.format_refinement_report(result)
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print(report)
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if result.success and len(result.actions_taken) > 0:
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return 0 # Success with changes
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elif result.success:
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return 1 # Success but no changes needed
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else:
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return 2 # Error
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except FileNotFoundError:
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print(f"Error: Schema file not found: {schema_path}")
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return 2
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except json.JSONDecodeError as e:
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print(f"Error: Invalid JSON in schema file: {e}")
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return 2
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except Exception as e:
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print(f"Error: {e}")
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return 2
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Reference in New Issue
Block a user