Podcast Transcript Fetcher logo

Podcast Transcript Fetcher

Organization
Varnan-Tech
podcast-transcript-fetcher

Use when fetching, searching, or analyzing transcripts from Lenny's Podcast, Dwarkesh Podcast, Cheeky Pint, 20VC, or A16z Podcast. Tier 2 (RSS+Groq Whisper) is the recommended approach -- fast, free, and most reliable. Also use when asked to "get transcript", "find episode", "summarize podcast", or "search podcast content". Do not use for general web scraping or non-podcast audio transcription.

Overview

PublisherVarnan-Tech
Repositoryopendirectory
Skill namepodcast-transcript-fetcher
Stars
674
Forks
74
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Varnan-Tech on GitHub. Read the source before you install it.

Installation

Install the Podcast Transcript Fetcher AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Varnan-Tech/opendirectory/tree/main/skills/podcast-transcript-fetcher
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git /tmp/opendirectory
mkdir -p .claude/skills
cp -r /tmp/opendirectory/skills/podcast-transcript-fetcher .claude/skills/podcast-transcript-fetcher
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Podcast Transcript Fetcher in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Podcast Transcript Fetcher on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Podcast Transcript Fetcher is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Podcast Transcript Fetcher

Fetch transcripts from 5 supported podcasts. Tier 2 (RSS+Groq Whisper) is the recommended approach -- fast, free, and the most reliable across all podcasts. Tier 1 free sources are best-effort (limited availability). Tier 3 Taddy API is the premium/commercial option.

Quick Reference

bash
# Get latest episode transcript (auto-detects best method)
python scripts/get_transcript.py "Lenny's Podcast" --latest

# Search by episode title or number
python scripts/get_transcript.py 20vc --episode "Marc Andreessen"
python scripts/get_transcript.py dwarkesh --episode 15

# Force specific method
python scripts/get_transcript.py "cheeky pint" --latest --method whisper
python scripts/get_transcript.py a16z --latest --method taddy

# Save to file
python scripts/get_transcript.py lennys --latest --output transcript.md

# List all supported podcasts
python scripts/get_transcript.py --list-podcasts

Supported Podcasts

PodcastTier 1 (best-effort)Tier 2 RSS+Whisper [RECOMMENDED]Tier 3 Taddy (premium)
Lenny's PodcastGitHub archive (269 transcripts)✅ Substack RSS✅ Covered
Dwarkesh PodcastWebsite scrape + Substack PDF✅ Substack RSS✅ Covered
Cheeky Pint(none)✅ Transistor.fm RSS✅ Covered
20VCSubstack PDF✅ Libsyn RSS✅ Covered
A16z PodcastWebsite scrape✅ Simplecast RSS✅ Covered

Implementation

1. Install Dependencies

bash
# Core (always required)
pip install requests

# Cloud transcription (recommended — fast, free tier)
pip install groq
export GROQ_API_KEY="your-key"  # Get at https://console.groq.com

# Local transcription (free, needs ~5GB RAM)
pip install faster-whisper

# Audio compression (for Groq's 25 MB limit — Windows: winget/scoop)
#   winget install ffmpeg  or  scoop install ffmpeg

# Taddy API (commercial, optional)
export TADDY_API_KEY="your-key"  # Get at https://taddy.org

2. Get a Transcript

The script auto-selects the best method. Tier 2 is the default recommendation:

Tier 1 → Tier 2 (RECOMMENDED) → Tier 3
(best-effort)  (Whisper)  (Taddy API premium)

Tier 1: Free direct sources (best-effort, limited availability)

  • Lenny's: Clones ChatPRD/lennys-podcast-transcripts and searches by title
  • Dwarkesh: Substack PDF scrape
  • 20VC: Substack PDF scrape
  • A16z: Website scrape
  • Cheeky Pint: No Tier 1 sources available
  • Note: Tier 1 sources are best-effort and limited. Tier 2 (RSS+Whisper) is the recommended approach.

Tier 2: RSS + Whisper transcription [RECOMMENDED]

  • Downloads MP3 from podcast RSS feed
  • Compresses if >25 MB (ffmpeg)
  • Transcribes via Groq Whisper API (free tier, ~10s per hour of audio)
  • Fast, free, and works for every podcast in the registry
  • Default recommendation for all use cases

Tier 3: Taddy API (commercial/premium)

  • Requires TADDY_API_KEY ($75/mo+)
  • Use for large-scale or production transcript needs
  • Covers all 5 podcasts with auto-transcription

3. Analyze with AI

Once you have a transcript, pipe it to the agent for analysis:

markdown
I have this transcript from [podcast]. Can you:
1. Summarize the key arguments
2. Extract 3 actionable insights
3. Identify any controversial claims
4. Compare with [other podcast] on the same topic

Supported Workflows

Single Episode

ScenarioCommand
Latest episodeget_transcript.py "Lenny's Podcast" --latest
Specific episode by titleget_transcript.py 20vc --episode "Sam Altman"
Episode by numberget_transcript.py dwarkesh --episode 42
Force Whisper transcription (Tier 2, recommended)get_transcript.py a16z --latest --method whisper
Force Taddy API (premium)get_transcript.py lennys --latest --method taddy
Save to Markdownget_transcript.py cheeky-pint --latest --output episode.md
JSON outputget_transcript.py dwarkesh --latest --json

Cross-Podcast Search & Batch

ScenarioCommand
Search all podcasts by keywordget_transcript.py --search "Marc Andreessen"
Search by guest nameget_transcript.py --guest "Sam Altman"
Search within one podcastget_transcript.py "Lenny's Podcast" --search "vibe coding"
Batch-transcribe last N episodesget_transcript.py "Dwarkesh Podcast" --last 5
Search + transcribe top matchesget_transcript.py --search "AI safety" --transcribe
Pipeline with custom countget_transcript.py --search "scaling laws" --transcribe --transcribe-count 5
Filtered search pipelineget_transcript.py "A16z Podcast" --search "crypto" --transcribe

Output Structure

Batch transcription saves to output/ with per-podcast subdirectories:

output/dwarkesh-podcast/Dwarkesh Podcast_2024-01-15_agi-is-still-30-years-away.md
output/20vc/20 Minutes VC (20VC)_2024-03-10_funding-round-analysis.md

Each file includes a YAML frontmatter header:

yaml
---
podcast: Dwarkesh Podcast
episode: AGI is still 30 years away
date: 2024-01-15
url: https://...
source: whisper
---

Podcast Registry

The registry at scripts/podcasts.json maps each podcast to its RSS feeds, transcript sources, and API endpoints. To add new podcasts:

json
{
  "id": "new-podcast",
  "name": "New Podcast",
  "rss": "https://example.com/feed.xml",
  "transcript_sources": {
    "primary": {"type": "website_scrape", "url": "https://example.com"}
  }
}

Troubleshooting

ProblemSolution
"No transcript found"Tier 2 (RSS+Whisper) is the recommended approach. If auto mode fails, try --method whisper to force it.
RSS fetch failsRSS feeds may change; check scripts/podcasts.json for current URLs
Audio download slowLarge MP3s can take minutes on slow connections
Groq rate limitedWait or switch to local faster-whisper
Taddy not returning transcriptsSome episodes lack transcripts; try --method whisper
Podcast not in registryAdd it to scripts/podcasts.json
Unicode error on WindowsFixed: script auto-reconfigures stdout to UTF-8; saved files use UTF-8 encoding
Audio > 25 MB for GroqInstall ffmpeg: winget install ffmpeg (Windows) or brew install ffmpeg (macOS)

RSS Feed Status (as of 2026-06)

PodcastOld Feed (broken)Current Feed
Cheeky Pintfeeds.transistor.fm/the-cheeky-pint (404)feeds.transistor.fm/cheeky-pint-with-john-collison
20VCfeeds.simplecast.com/3GxrMqOd (404)feeds.libsyn.com/61840/rss
A16zfeeds.simplecast.com/0cJfpoz2 (404)feeds.simplecast.com/JGE3yC0V

Common Mistakes

  • Forgetting API keys: Set GROQ_API_KEY in your env or .env file
  • Relying on Tier 1 free sources: Tier 1 is best-effort and limited. Always fall back to Tier 2 (RSS+Whisper) which is the recommended method.
  • Not cloning the Lenny's repo first: The GitHub archive must be cloned locally for Tier 1 to work
  • Using --method taddy without TADDY_API_KEY: Falls through silently; set the key or use auto mode

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Podcast Transcript Fetcher AI skill do?

Use when fetching, searching, or analyzing transcripts from Lenny's Podcast, Dwarkesh Podcast, Cheeky Pint, 20VC, or A16z Podcast. Tier 2 (RSS+Groq Whisper) is the recommended approach -- fast, free, and most reliable. Also use when asked to "get transcript", "find episode", "summarize podcast", or "search podcast content". Do not use for general web scraping or non-podcast audio transcription.

Why use Podcast Transcript Fetcher on TypingMind?

Because you install it once and use it with any model. Podcast Transcript Fetcher is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Podcast Transcript Fetcher in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Varnan-Tech/opendirectory/tree/main/skills/podcast-transcript-fetcher. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Podcast Transcript Fetcher?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Podcast Transcript Fetcher?

As many as you like. As long as a model supports skills, you can use Podcast Transcript Fetcher with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Podcast Transcript Fetcher AI skill free?

Yes. It is published on GitHub by Varnan-Tech under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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