A powerful tool for searching podcast transcripts and retrieving episode metadata via semantic search.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install podsips-search
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install podsips-search using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is PodSips Podcast Search?
PodSips Search is a specialized integration designed to bridge the gap between AI agents and the vast world of audio content. By leveraging the PodSips API, this Openclaw Skills implementation enables semantic searching across indexed podcast transcripts, allowing users to find specific clips, quotes, and discussions with high accuracy. It goes beyond simple keyword matching by understanding the context of conversations to provide relevant segments from thousands of episodes.
This skill is essential for researchers, content creators, and developers who need to ground their AI's responses in real-world podcast data. Whether you are looking for specific industry insights, celebrity interviews, or niche technical discussions, PodSips provides the structured data needed to summarize, cite, or analyze podcast content effectively within an automated workflow.
PodSips Podcast Search Use Cases
- Searching for specific topics or mentions within thousands of podcast episodes using natural language.
- Retrieving full transcripts for deep-dive analysis, summarization, or translation tasks.
- Fact-checking claims by finding the exact moment a statement was made on air.
- Monitoring industry trends and expert opinions across multiple podcast series automatically.
- Expanding context around search results to understand the full flow of a conversation.
How PodSips Podcast Search Works
- The AI agent receives a user query related to podcast content or specific episode data.
- A semantic search is performed via the PodSips API to identify relevant transcript chunks and timestamps.
- The skill retrieves metadata including speaker names, episode titles, and series descriptions.
- If additional context is needed, the agent calls the context or full transcript endpoints to gather more data.
- The structured results are then processed and presented with proper citations and deep links.
PodSips Podcast Search Setup
To begin using this skill, ensure you have a PodSips API key and the necessary environment variables configured.
- Sign up at https://developer.podsips.com using Google.
- Generate an API Key from the dashboard (this key is only shown once).
- Export the key as an environment variable in your shell:
export PODSIPS_API_KEY="ps_live_your_key_here"
- Verify the setup using this command:
test -n "$PODSIPS_API_KEY" && echo "API key is set"
PodSips Podcast Search Data Schema & Taxonomy
The skill interacts with JSON-formatted data representing various podcast entities. This Openclaw Skills component organizes data into the following structures:
| Object | Description |
|---|---|
| Search Chunk | Contains transcript text, start/end timestamps, and speaker identification tags. |
| Episode | Metadata including title, description, publish date, audio URLs, and duration. |
| Series | High-level information like podcast name, genre, image URLs, and RSS feeds. |
| Context | Segmented transcript lines appearing immediately before and after a target timestamp. |
| Request Status | Tracking data for newly submitted podcasts, including status such as pending or complete. |
PodSips Podcast Search Advanced Features
- Semantic search filtering by series UUID, episode UUID, or specific speaker names.
- Deep-linking support using the podsips:// protocol for seamless mobile app integration.
- Automated request system for indexing missing podcasts with status tracking.
- Precise speaker diarization with support for mapping generic labels to real identities.
- Chronological full transcript retrieval optimized for long-form content analysis.
SKILL.md
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