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transcript-polisher成绩单抛光机

Agent Skill

transcript-polisher 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

574

周安装

23

GitHub Stars

4

下载量

186
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:transcript-polisher(成绩单抛光机)
来源仓库:https://github.com/cdeistopened/opened-vault
仓库路径:skills/transcript-polisher
安装命令:
npx skills add https://github.com/cdeistopened/opened-vault --skill transcript-polisher
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/cdeistopened/opened-vault --skill transcript-polisher

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。
  • 建议结合原始 README 核验具体用法和功能边界。

SKILL.md

Transcript Polisher

Transform raw podcast or interview transcripts into polished, professional documents that maintain authentic voice while dramatically improving readability and flow.

When to Use This Skill

Use this skill when:

  • Processing raw podcast transcripts from automated services (Rev, Otter, Descript, YouTube auto-captions)
  • Cleaning up interview recordings or video transcripts
  • Preparing spoken content for publication as articles or show notes
  • Converting conversational content into readable written format

Not for: Written content that wasn't originally spoken, pre-polished articles, or scripts that are already edited.

Core Philosophy

Balance authenticity with clarity: Remove everything that doesn't add meaning while preserving what was actually said. Create the "ideal version" of what the speaker wanted to communicate—without changing their words or ideas.

Target: 25-35% length reduction while maintaining 100% fidelity to meaning.

Workflow

Step 1: Add Document Structure

Create proper header with:

# [Guest Name]: [Compelling Episode Title]

*[Podcast Name] Episode - [Host Names]*

---

## Timestamped Outline
[Add 10 chapters maximum - see guidelines below]

---

## [Time] Chapter Title
[Content starts here]

Timestamped Outline Rules (My First Million style):

  • Format: **MM:SS** - Descriptive Chapter Title
  • 10 chapters maximum for 45-60 minute episodes
  • Focus on major topic changes, not minute-by-minute
  • Use compelling, specific titles (not generic descriptions)

Good Examples:

  • 12:25 - The 13th Percentile to Grade Level Miracle
  • 29:08 - Why Successful Reforms Don't Spread

Poor Examples:

  • 12:25 - Michelle talks about her students
  • 29:08 - Discussion about education reform

Step 2: Identify and Label Speakers

Replace generic speaker markers (>>, Speaker 1, etc.) with actual names:

  • Bold all speaker names: **Isaac:** Content here
  • Use first names for casual podcasts, full names for professional interviews
  • Be consistent throughout

Step 3: Aggressive Editing Pass

Apply aggressive polishing while maintaining 100% fidelity. See Editing Guidelines for detailed rules.

Quick checklist:

  • Remove ALL filler words ("um," "uh," "you know," "like," "so," "I mean")
  • Consolidate false starts and restarts
  • Pick the clearest version when speakers repeat themselves
  • Remove verbal hedging ("kind of," "sort of," "I think," "probably") when excessive
  • Cut conversational detours that don't serve the narrative
  • Fix awkward grammar and incomplete thoughts
  • Keep only 1-2 strongest examples if speaker gives 5+
  • Add clarity to vague pronouns (minimal bracketed additions)

Step 4: Preserve What Matters

Never edit:

  • Unique voice and natural rhythm
  • Exact wording of powerful statements
  • Emotional moments and authenticity
  • Specialized terminology
  • Cultural references that reveal personality
  • Natural dialogue patterns

Step 5: Quality Check

Before finishing:

  • Length reduced by 25-35%
  • All filler words removed
  • Speakers properly identified
  • Chapter breaks added with compelling titles
  • Grammar fixed but voice preserved
  • Key insights and stories intact
  • No meaning changed or paraphrased

Quick Reference

For detailed examples and transformation patterns, see:

Common Transcription Errors to Fix

Auto-caption issues:

  • OCR errors (e.g., "quad code" → "Claude Code")
  • Homophone mistakes (e.g., "their" vs "there")
  • Missing punctuation
  • Run-on sentences
  • Mis-identified technical terms

Audio transcription issues:

  • Speaker confusion
  • Overlapping dialogue
  • Background noise artifacts
  • Timestamp errors

Output Format

Final polished transcript should be:

  • Markdown formatted
  • Properly sectioned with timestamps
  • Speaker names bold and consistent
  • 25-35% shorter than original
  • Grammar perfect but voice authentic
  • Ready for publication or repurposing

Critical Reminders

100% Fidelity Rule: ❌ Never paraphrase or change meaning ❌ Never add ideas not present in original ❌ Never remove key insights or stories ✅ Only remove redundancy and inefficiency ✅ Preserve exact wording of powerful statements ✅ Keep all substantive content

Aggressive Editing: ❌ "So, um, I think that, you know, what we really need to focus on..." ✅ "What we really need to focus on..."

Voice Preservation: ❌ Removing authentic expressions like "bugged the crap out of me" ✅ Keeping natural language that shows personality

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.92%
按下载量换算69

Claude

30.06%
按下载量换算56

Cursor

19.53%
按下载量换算36

Gemini CLI

9.01%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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