ark-context-warmup

To load recent project context before an Ark workflow chain, invoke a context warm-up process at step 0. This automatically generates and caches a Context Brief using recent data from NotebookLM vaults, vault wiki queries, and TaskNotes to ensure up-to-date signals.

Context warm-up is the process of loading relevant project data before a chain starts to prevent stale session recovery. It prepares a deterministic Context Brief by querying NotebookLM vaults and TaskNotes, ensuring decisions are based on current signals.

Yes, you can use NotebookLM vaults and TaskNotes together to prepare context for automation workflows. The system applies a multi-backend discovery workflow that queries both sources to build a comprehensive Context Brief for your run.

Yes, context caching works seamlessly with frontmatter-driven context loading in project automation. The system implements deterministic outputs by caching the Context Brief, allowing you to refresh context on demand without repeatedly querying the vault index.

The best way to improve cross-project context transfer when starting new chains is to trigger an automatic context warm-up at step 0. This reduces misalignment by loading relevant data from NotebookLM vaults and TaskNotes into a fresh Context Brief.

Yes, you need the pyyaml dependency installed to run frontmatter-driven context loading for vault index queries. This library enables the Python scripts to parse frontmatter data and execute the multi-backend discovery workflow correctly.