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Hybrid regex-and-LLM framework for parsing structured text, optimizing cost by handling 95–98% with regex and reserving LLM calls for edge cases. \n \n Combines regex extraction with confidence scoring to flag low-confidence items, then validates only those items with an LLM, reducing LLM calls by ~95% versus all-LLM approaches \n Includes production-ready Python patterns for regex parsing, confidence scoring, and hybrid pipeline orchestration with real metrics from a 410-item quiz parsing examp

Implementation agent that executes predefined plans step-by-step without deviation. \n \n Requires an explicit implementation plan document as input; returns an error message if none is provided \n Follows the plan sequentially, checking off completed items and refusing to skip steps or add unspecified code \n Updates the plan document inline as progress is made and validates work using build or test commands specified in the plan \n Stops execution when reaching STOP instructions and returns co

Generates complete, copy-paste ready implementation documentation from structured PR plans. \n \n Parses feature plans to extract implementation steps, affected files, and requirements \n Produces comprehensive markdown documentation with full code blocks, exact file paths, and zero-ambiguity instructions \n Includes research-backed code patterns, project conventions, and technology stack details specific to your codebase \n Provides markdown checkboxes, verification checklists, and commit gates

Structured planning framework for breaking development requests into testable, commit-sized implementation steps. \n \n Conducts mandatory autonomous research phase to gather code context, documentation, dependencies, and existing patterns before planning \n Breaks features into commits sized for single pull requests, with simple features consolidated into one commit and complex features split into multiple testable steps \n Generates plans with file lists, step descriptions, and verification me