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transcribe-and-analyze转录和分析

Agent Skill

transcribe-and-analyze 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

685

周安装

28

GitHub Stars

175

下载量

220
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

3

许可证

MIT

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:transcribe-and-analyze(转录和分析)
来源仓库:https://github.com/nicepkg/ai-workflow
仓库路径:skills/transcribe-and-analyze
安装命令:
npx skills add https://github.com/nicepkg/ai-workflow --skill transcribe-and-analyze
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/nicepkg/ai-workflow --skill transcribe-and-analyze

简介

transcribe-and-analyze 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 中整理协作事项。

  • 适用于围绕仓库状态、代码变更或团队协作进行信息梳理。
  • 通过 npx skills add 命令从 GitHub 仓库安装使用。
  • 安装前需确认权限范围、维护状态及是否触发联网或文件操作。
  • 建议结合原始 README 文档进一步验证具体用法和功能边界。

SKILL.md

Transcribe and Analyze

Local transcription of audio/video content using WhisperKit. Analysis is available on request using OpenAI or local Ollama.

Capabilities

  1. Transcription - Convert audio/video URLs to text using WhisperKit (runs locally, always available)
  2. Analysis - Extract insights from transcripts (only when user asks for it, supports OpenAI or Ollama)

Quick Start

Transcribe Only

python3 scripts/transcribe.py "https://youtube.com/watch?v=..."

Transcribe + Analyze (OpenAI)

python3 scripts/transcribe.py "https://youtube.com/watch?v=..."
python3 scripts/analyze_transcript.py whisper-transcriptions/video.md

Transcribe + Analyze (Local)

python3 scripts/transcribe.py "https://youtube.com/watch?v=..."
python3 scripts/analyze_transcript.py whisper-transcriptions/video.md --local

Transcription

Script Options

# Basic
python3 scripts/transcribe.py "URL"

# Custom output directory
python3 scripts/transcribe.py "URL" --output-dir "/path/to/save"

# Higher accuracy (slower)
python3 scripts/transcribe.py "URL" --model medium

# Without timestamps
python3 scripts/transcribe.py "URL" --no-timestamps

# Custom filename
python3 scripts/transcribe.py "URL" --filename "my-transcription.md"

Whisper Models

ModelSpeedAccuracyUse Case
tinyFastestLowestQuick drafts, testing
baseFastReasonableSimple content
smallBalancedGoodDefault - most use cases
mediumSlowerHighLectures, important content
largeSlowestHighestCritical accuracy needed

Dependencies

Script checks for these and provides install instructions if missing.

Output

Transcriptions save to ./whisper-transcriptions/ as markdown:

# Transcription

**Source:** https://youtube.com/watch?v=example
**Transcribed:** 2025-01-15 14:30:00
**Tool:** WhisperKit

---

[00:00:00.000 --> 00:00:05.000] Welcome to this video...

Analysis

Provider Options

OpenAI API (default):

python3 scripts/analyze_transcript.py transcript.md
python3 scripts/analyze_transcript.py transcript.md --model gpt-4o

Requires OPENAI_API_KEY environment variable.

Local Ollama:

python3 scripts/analyze_transcript.py transcript.md --local
python3 scripts/analyze_transcript.py transcript.md --local --model mistral

Requires Ollama running (ollama serve).

Script Options

# Default comprehensive analysis (OpenAI)
python3 scripts/analyze_transcript.py transcript.md

# Use local Ollama
python3 scripts/analyze_transcript.py transcript.md --local

# Specify model
python3 scripts/analyze_transcript.py transcript.md --model gpt-4o
python3 scripts/analyze_transcript.py transcript.md --local --model llama3.2

# Custom analysis prompt
python3 scripts/analyze_transcript.py transcript.md --prompt "List all tools mentioned"

# Custom output location
python3 scripts/analyze_transcript.py transcript.md --output ~/Documents/analysis.md

# Print to stdout instead of saving
python3 scripts/analyze_transcript.py transcript.md --print

Default Analysis Includes

  • Executive summary (2-3 paragraphs)
  • Key insights (5-7 bullet points)
  • Topics discussed with summaries
  • Notable quotes (3-5 memorable quotes)
  • Action items and recommendations
  • Additional observations

Custom Prompt Examples

--prompt "List all technologies and tools mentioned"
--prompt "What are the main arguments presented?"
--prompt "Extract all statistics and data points"
--prompt "Summarize in 5 bullet points"
--prompt "What questions were asked and how were they answered?"

Dependencies

  • openai - pip install openai (used for both OpenAI and Ollama)
  • OPENAI_API_KEY environment variable (for OpenAI only)
  • Ollama running locally (for --local mode)

Output

Analysis saves alongside transcript as transcript_name_analysis.md:

# Transcript Analysis

**Source Transcript:** path/to/transcript.md
**Analysis Model:** gpt-4o-mini (OpenAI)
**Tokens Used:** 33,763

---

[Analysis content]

Common Workflows

Full Pipeline: URL to Insights (Cloud)

python3 scripts/transcribe.py "https://youtube.com/watch?v=abc123"
python3 scripts/analyze_transcript.py whisper-transcriptions/watch.md

Full Pipeline: URL to Insights (Local)

python3 scripts/transcribe.py "https://youtube.com/watch?v=abc123"
python3 scripts/analyze_transcript.py whisper-transcriptions/watch.md --local

Multiple Analyses on Same Transcript

python3 scripts/analyze_transcript.py transcript.md --output summary.md
python3 scripts/analyze_transcript.py transcript.md --prompt "List action items" --output actions.md
python3 scripts/analyze_transcript.py transcript.md --prompt "Extract quotes" --output quotes.md

Batch Transcription

python3 scripts/transcribe.py "URL1"
python3 scripts/transcribe.py "URL2"
python3 scripts/transcribe.py "URL3"

Reference Files

Troubleshooting (references/troubleshooting.md)

  • Download failures
  • Transcription errors
  • Dependency issues
  • API errors

Configuration (references/configuration.md)

  • Output format details
  • File naming behavior
  • Model selection guidance

Usage Patterns (references/usage-patterns.md)

  • Common transcription scenarios
  • Analysis patterns
  • Batch processing tips

Scripts

ScriptPurpose
scripts/transcribe.pyDownload and transcribe audio/video from URLs (WhisperKit)
scripts/analyze_transcript.pyAI analysis of transcript files (OpenAI or Ollama)

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenCode

30.35%
按下载量换算67

Claude Code

22.76%
按下载量换算50

Cursor

17.94%
按下载量换算39

Gemini CLI

14.34%
按下载量换算32

goose

9.4%
按下载量换算21

github-copilot

3.94%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。

来源信息

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