dojo-node-grinder

You can automate batch creation of knowledge graph nodes by processing grind-targets.json through a script-backed grinder that drives autonomous generation, applies priority filtering, and executes parallel packaging.

Autonomous node generation is the process of expanding a knowledge graph by discovering missing ecosystem nodes via frontmatter-defined schemas and automatically validating the resulting node trees for consistency.

To scale knowledge graph expansion, you use a grind-targets configuration that supports parallel execution, retry logic, and loop mode to systematically process and package multiple nodes simultaneously.

Yes, you need jq installed as a dependency, because the script relies on it to parse frontmatter-defined schemas and process the grind-targets JSON file during batch node execution.

Yes, priority filtering and retry logic are supported during node packaging, allowing you to manage execution order and automatically recover from failures when processing large batches of targets.

Script-backed node tree validation is limited to enforcing discovery through frontmatter-defined schemas, meaning it only validates structural consistency and does not verify the semantic accuracy of the generated research-backed content.