Can it handle multiple speakers?

Yes, it identifies and labels speakers consistently using bold markers and can transition from generic placeholders like 'Speaker 1' to actual names provided in the context.

What kind of length reduction should I expect?

Typically, the skill reduces transcript length by 25-35% by eliminating verbal tics, false starts, and redundant explanations that occur naturally in speech.

Does this skill change the meaning of what was said?

No, the skill follows a strict 100% fidelity rule, removing only redundancy and fillers while preserving every key insight and the speaker's original intent.

Is it suitable for technical interviews?

Absolutely. It is designed to preserve specialized terminology and domain-specific language while fixing the awkward grammar common in spoken technical dialogue.

Transcript Polisher

Name: Transcript Polisher
Author: cdeistopened

bycdeistopened

•

Content Management

Transforms raw, rambling podcast and interview transcripts into professional, structured documents while preserving the speaker's authentic voice.

Transcript Polisher is a specialized Claude Code Skill designed to bridge the gap between messy automated transcriptions and publish-ready content. It systematically removes filler words, fixes grammatical errors, and organizes spoken dialogue into clear chapters with timestamps, achieving a 25-35% reduction in length without altering the original meaning. This skill is ideal for content creators, journalists, and researchers who need to convert raw audio-to-text data into readable articles, show notes, or internal documentation while maintaining 100% fidelity to the speaker's intent and personality.

Key Features

01Markdown structure generation with timestamped outlines

02Aggressive editing for clarity with 100% fidelity to meaning

03Intelligent speaker identification and consistent bold labeling

041 GitHub stars

05Automated filler word removal (um, uh, you know, etc.)

06Voice preservation to keep unique personality and tone intact

Use Cases

01Creating structured show notes and chapter markers for podcast episodes

02Converting raw Otter or Rev transcripts into polished blog posts or articles

03Cleaning up interview recordings for qualitative research or documentation

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add cdeistopened/skill-stack transcript-polisher

For use in Claude.ai and ChatGPT

Download Skill