| name | SAI-podcast-download |
| description | Atomic SAI skill. Download podcast episode audio from an RSS feed or a Spotify show URL (resolved to RSS via the iTunes Search API — Spotify itself blocks audio downloads). Resume-safe, retry-aware. Emits a manifest.json that downstream skills (local-transcribe, podcast-rag-index) consume. Use whenever you need to download a podcast, grab episodes of a show, pull audio for a Spotify show URL, or any workflow needs raw podcast MP3s as input. |
Trigger manifest — podcast-download (atomic, autonomous)
Code: skills/podcast-download/
Manifest: skill.yaml (4-tier cascade)
Entry point: runner.py → run(inputs)
Cascade plan
1. resolve_feed (rules) → Spotify URL → RSS via iTunes Search API
2. list_episodes (rules) → parse RSS, filter by since_date / max_episodes
3. download_each (rules) → fetch missing audio (retries, resume-safe)
4. write_manifest (rules) → emit manifest.json; ready_to_propose
All tiers are deterministic Python. No LLM calls. No external auth required.
Invocation
.venv/bin/python3.12 \
skills/podcast-download/runner.py run \
--inputs-json '{
"spotify_show_url": "https://open.spotify.com/show/<spotify-show-id>",
"output_dir": "~/Media/podcasts/<show-slug>",
"since_date": "2020-01-01",
"max_episodes": 0
}'
Either spotify_show_url or feed_url is required. max_episodes: 0 means all.
Invoke runners by absolute path (folder names use hyphens, so python -m won't import).
Standard manifest shape
{
"workflow_id": "podcast-download",
"feed_url": "https://.../feed.xml",
"episodes": [
{
"episode_id": "<sha1-hex>",
"title": "...",
"pub_date": "YYYY-MM-DD",
"audio_path": "/abs/path/to/file.mp3",
"audio_url": "https://...",
"show_title": "..."
}
],
"download_results": {"downloaded": [...], "skipped": [...], "failed": [...]}
}
Composes with
SAI-local-transcribe — feeds manifest.episodes[].audio_path into WhisperSAI-podcast-rag-index — writes transcripts into the ChromaDB index
