| name | SAI-podcast-rag-index |
| description | Atomic SAI skill. Index a directory of transcript .md files (YAML frontmatter, one per episode) into an existing ChromaDB RAG store by delegating to a rag-index-updater-style index.py. Pure mechanism — no operator paths or collection baked in; the caller supplies indexer_scripts / manifest_path directly or via a private config_path. Hash-skips unchanged files. Use whenever you need to index transcripts, add transcripts to a RAG, or embed episodes for semantic lookup. |
Trigger manifest — podcast-rag-index (atomic, autonomous)
Code: skills/podcast-rag-index/
Manifest: skill.yaml (3-tier cascade)
Entry point: runner.py → run(inputs)
Cascade plan
1. locate_indexer (rules) → resolve indexer_scripts (input or config_path); fail-closed if unset
2. scan_inputs (rules) → diff input_dir vs manifest (new+changed only)
3. run_indexer (rules) → shell to index.py → ChromaDB upsert
Invocation
.venv/bin/python3.12 \
skills/podcast-rag-index/runner.py run \
--inputs-json '{
"input_dir": "~/Media/transcripts/<show-slug>",
"config_path": "<your-private-overlay>/config/podcast_ingest.yaml"
}'
config_path supplies operator values (indexer_scripts, manifest_path) from
the private side. Or pass indexer_scripts directly. "force": true re-indexes
even if hash unchanged. Invoke by absolute path (hyphenated folder name).
Why a thin wrapper
The operator's index.py owns embed + chunk + upsert + the ChromaDB collection.
This skill only scopes the scan to one directory and reuses that indexer — one
source of truth, no second codepath to drift.
Composes with
- Upstream:
SAI-local-transcribe
- Companion: a general-purpose
rag-index-updater (full-tree variant)
- Downstream consumer: a
rag-content-lookup (semantic search over results)
