| name | gcp-agent-golden-dataset-builder |
| description | Assists developers in collecting and structuring a library of diverse examples ("Golden Dataset") required for data-driven evaluation, including tool trajectories. |
gcp-agent-golden-dataset-builder
This skill helps you build the foundation for data-driven agent development: the Golden Dataset. Grounded in evaluation_blog.md, it focuses on verifying not just the final answer, but the "Thinking Process" (Reasoning Trace).
Usage
Ask Antigravity to:
- "Build a golden dataset with tool trajectories"
- "Structure my evaluation data for tool call validation"
- "Create a template for my Course Creator agent evaluation"
Dataset Pattern
A production-ready dataset uses the .jsonl format and includes:
prompt: The user input.reference: The ground truth answer (for semantic ResponseMatch).reference_trajectory: A list of expected tool calls. This allows the evaluator to check if the agent used the right tools in the right order.
Example Structure
Refer to examples/trajectory_dataset.jsonl for the implementation. Note the use of tool_name and tool_input in the trajectory.
