What problem does it solve? Applying the same edit to hundreds of entries in a large file is slow and error-prone when done sequentially, and letting multiple agents edit one file causes conflicts. This Skill splits large files into entry-aligned chunks, processes them with parallel subagents, and reassembles the results safely. ## Core Features & Use Cases - Chunked Parallel Processing: Splits files at entry boundaries (TOML arrays, Markdown sections, JSON elements) and processes chunks with up to 5 concurrent subagents. - Two I/O Modes: Transform mode edits chunks in place; generate mode reads input chunks and writes results to separate output files. - Autonomous Parameter Inference: Detects delimiters, batch sizes, and model choice (Sonnet vs. Opus) without asking the user. - Use Case: Rewrite a field in every entry of a 500-entry TOML config file, or generate descriptions for every item in a large Markdown catalog, in a fraction of the sequential time. ## Quick Start Apply this transformation to every entry in my large config file using parallel batch editing.