What does this skill do?

The Hybrid Regex and LLM Parser Skill resolves the dilemma of choosing between regex and language models for extracting structured text. The core strategy uses regex for 95–98% of cases in a deterministic and cost-effective manner, reserving the LLM exclusively for edge cases where extraction confidence is low. It includes confidence scoring, automatic filtering, and selective validation using cost-effective models.

Questionnaire Analysis
Extract questions, options, and answers from questionnaires with a repetitive format using regex patterns.
Trust Score
It evaluates each excerpt based on criteria such as the number of options, the presence of a response, and the length of the text.
Selective Validation with LLM
Send only items with a confidence level below 0.95 to the LLM, reducing calls and costs by 95%.
High-Volume Processing
Process invoices, forms, and scaled tables without sending all the content to the LLM.

Usage examples

📋 Questionnaire analysis
Parse this questionnaire using regular expressions and return the items along with their confidence scores.
🔍 Review low confidence
Extract the questions from this form and flag those with a confidence level below 0.95 for review by LLM.
📊 Process a batch of invoices
Process these 410 invoices using the hybrid pipeline and tell me how many required validation with the LLM.
🧩 Complete pipeline
Build a pipeline that combines regex and LLM to extract structured data from this document.

Features

Regex-First Strategy It resolves 95–98% of cases deterministically without making calls to the LLM.
Automatic Confidence Score It evaluates each answer by penalizing missing options, blank answers, and short responses.
Selective LLM Validation Only elements with a confidence level below the threshold are sent to the most economical model available.
Immutability of Objects The elements corrected by the LLM are integrated without altering the original instances in the parser.
95% cost savings Out of 410 items in production, only 8 required review, and 5 calls were made to the LLM.

Frequently asked questions

Not necessarily. The pipeline works with regex alone; the LLM is only used if there are low-confidence elements and an LLM client is provided.
The default threshold is 0.95. Items with scores below this threshold are flagged for validation by the LLM.
Any text structured with repetitive patterns: questionnaires, forms, tables, invoices, and similar documents.
In a real-world case involving 410 items, the regex achieved a 98% success rate, and only 5 calls were made to the LLM, resulting in a 95% cost savings.
Hybrid Regex and LLM Parser — Efficient Text Extraction with Claude AI

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