What problem does it solve?
ASR transcripts contain homophone errors, misspelled English product names, casing drift, and filler words that make them unpublishable. This Skill proofreads raw transcripts against a user-maintained dictionary, fixing only high-confidence errors while preserving the original wording, and produces a traceable correction log.
Core Features & Use Cases
- Dictionary-Guided Correction: Reads a YAML user dictionary of target terms (product names, legal terms, personal names) and replaces mis-transcriptions only when context, dictionary entry, and form-drift evidence all align.
- Lossless Cleanup by Default: Removes filler words (呃/啊/那个), normalizes whitespace and punctuation spacing, and converts TXT speaker-timestamp blocks to Markdown without altering meaning.
- Optional Polishing Phase: Config-flagged steps merge consecutive speaker blocks, normalize punctuation, split long paragraphs, insert H2 topic headings, and embed per-chapter summaries.
- Use Case: A lawyer receives a raw transcript of a client meeting or AI training session. The Skill outputs a corrected Markdown file mirrored next to the source, plus an archived correction log listing every replacement, deletion, and skipped low-confidence item.
Quick Start
Proofread the attached ASR transcript using my user dictionary and output the corrected Markdown with a full correction log.