Cursor Extractor -

def __init__(self, schema: Dict[str, str]): self.schema = schema # field -> regex pattern self.results = []

Extract from the selected log file: - Timestamp (ISO format) - Error level (ERROR/WARN/INFO) - Message summary (max 50 chars) - Component name Return as JSON array.

import re import json from pathlib import Path from typing import Dict, Any class CursorExtractor: """Hybrid regex + placeholder for AI refinement""" Cursor Extractor

inside Cursor Composer today: “Extract all email addresses and dates from the selected text. Output JSON.”

That’s your first extraction. From there, build your own extractor library. def __init__(self, schema: Dict[str, str]): self

def extract_from_text(self, text: str, file_path: str = None): entry = "_source": file_path for field, pattern in self.schema.items(): match = re.search(pattern, text, re.IGNORECASE | re.MULTILINE) entry[field] = match.group(1) if match else None self.results.append(entry) return entry

extractor.save("extractor/output/structured_logs.json") From there, build your own extractor library

find data/raw -name "*.log" | entr -r python extractor/run_extractor.py Then ask Cursor AI: “Show me the diff of extracted errors between the last two runs.” Cursor Extractor can output to: