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Generation Tools

Generation tools help your AI assistant produce output grounded in your codebase structure. Rather than generating code from scratch, these tools use indexed knowledge about your symbols, dependencies, and patterns to create contextually accurate test scaffolding and upgrade recommendations.

Generate test scaffolding for a symbol or module. Returns a test skeleton based on the symbol’s signature, dependencies, and usage patterns - giving you a starting point that reflects the actual code structure.

Name Type Required Description
fqn string Yes Fully qualified name of the symbol to generate tests for
workspace_id string No Limit results to a specific workspace
repo_id string No Limit results to a specific repository
framework string No Test framework preference (e.g. junit, pytest, jest, testing)

“Generate tests for the PaymentService”

The assistant calls test_scaffold_gen and returns test scaffolding that includes the correct imports, mock setup for dependencies, and test cases covering the symbol’s public methods. The scaffold uses the specified test framework conventions and reflects the actual method signatures and dependency injection patterns found in the indexed code.


Get upgrade recommendations for dependencies in your project. Analyzes your current dependency versions against known updates and returns actionable recommendations with risk assessments.

Name Type Required Description
workspace_id string No Limit results to a specific workspace
repo_id string No Limit results to a specific repository
dependency string No Check a specific dependency (e.g. spring-boot, react, express)

“What should I upgrade in this project?”

The assistant calls upgrade_advisor and returns a prioritized list of dependencies that have available updates, along with the current version, latest version, and notes on breaking changes or migration steps.