ai-ml/dev-signal/.agent/skills/gcp-agent-golden-dataset-builder/SKILL.md
Assists developers in collecting and structuring a library of diverse examples ("Golden Dataset") required for data-driven evaluation, including tool trajectories.
npx skillsauth add googlecloudplatform/devrel-demos gcp-agent-golden-dataset-builderInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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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).
Ask Antigravity to:
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.Refer to examples/trajectory_dataset.jsonl for the implementation. Note the use of tool_name and tool_input in the trajectory.
devops
Standardizes the creation of Sensitive Data Protection (DLP) templates for PII and credential redaction.
development
Implements the "Defense-in-Depth" integration pattern in Python (intercepting prompts, parsing filter results).
testing
Configures Model Armor security policies (Prompt Injection, Jailbreak, RAI filters).
tools
Provides templates for configuring Vertex AI Gen AI Evaluation metrics like GROUNDING, TOOL_USE_QUALITY, and ResponseMatch for specific agent domains.