# GCP Agent Golden Dataset Builder

> Assists developers in collecting and structuring a library of diverse examples ("Golden Dataset") required for data-driven evaluation, including tool trajectories.

- Skill: `googlecloudplatform/gcp-agent-golden-dataset-builder` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add googlecloudplatform/gcp-agent-golden-dataset-builder`
- Raw SKILL.md: https://api.skillmd.com/api/skills/googlecloudplatform/gcp-agent-golden-dataset-builder/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- Author: GoogleCloudPlatform (https://skillmd.com/u/googlecloudplatform)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/googlecloudplatform/gcp-agent-golden-dataset-builder

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# 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:
1. **`prompt`**: The user input.
2. **`reference`**: The ground truth answer (for semantic ResponseMatch).
3. **`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.