explain-expert

Terraform infrastructure specialist for Vertex AI services and Gemini deployments. Provisions Model Garden, endpoints, vector search, pipelines, and enterprise AI infrastructure. Triggers: "vertex ai terraform", "gemini deployment terraform", "model garden infrastructure", "vertex ai endpoints"

Validate production readiness of Vertex AI Agent Engine deployments across security, monitoring, performance, compliance, and best practices. Generates weighted scores (0-100%) with actionable remediation plans. Use when asked to validate a deployment, run a production readiness check, audit security posture, or verify compliance for Vertex AI agents. Trigger with "validate deployment", "production readiness", "security audit", "compliance check", "is this agent ready for prod", "check my ADK agent", "review before deploy", or "production readiness check". Make sure to use this skill whenever validating ADK agents for Agent Engine.

Model Explainability Tool - Auto-activating skill for ML Training. Triggers on: model explainability tool, model explainability tool Part of the ML Training skill category.

Build production Firebase Genkit applications including RAG systems, multi-step flows, and tool calling for Node.js/Python/Go. Deploy to Firebase Functions or Cloud Run with AI monitoring. Use when asked to "create genkit flow" or "implement RAG". Trigger with relevant phrases based on skill purpose.

Terraform infrastructure specialist for deploying Genkit applications to production. Provisions Firebase Functions, Cloud Run services, GKE clusters, monitoring, and CI/CD for Genkit AI workflows. Triggers: "deploy genkit terraform", "genkit infrastructure", "firebase functions terraform", "cloud run genkit"

Generate production-ready Google Cloud code examples from official repositories including ADK samples, Genkit templates, Vertex AI notebooks, and Gemini patterns. Use when asked to "show ADK example" or "provide GCP starter kit". Trigger with relevant phrases based on skill purpose.

Build this skill enables AI assistant to provide interpretability and explainability for machine learning models. it is triggered when the user requests explanations for model predictions, insights into feature importance, or help understanding model behavior... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

Terraform infrastructure specialist for Vertex AI ADK Agent Engine production deployments. Provisions Agent Engine runtime, Code Execution Sandbox, Memory Bank, VPC-SC, IAM, and secure multi-agent infrastructure. Triggers: "deploy adk terraform", "agent engine infrastructure", "adk production deployment", "vpc-sc agent engine"

Generate a specialized domain-expert research agent modeled on PaperClaw architecture. Use this skill when a user wants to create an AI agent that can automatically search, filter, summarize, and evaluate academic papers in a specific research field. Trigger phrases include help me create a paper tracking agent for my field, I want an agent to monitor latest papers in bioinformatics, build me a paper review agent for computer vision, create a PaperClaw-style agent for my domain, generate a domain-specific paper expert agent. The generated agent is a complete OpenClaw agent with all required skills (arxiv-search, semantic-scholar, paper-review, daily-search, weekly-report) fully adapted for the target domain.

This skill should be used when establishing comprehensive QA testing processes for any software project. Use when creating test strategies, writing test cases following Google Testing Standards, executing test plans, tracking bugs with P0-P4 classification, calculating quality metrics, or generating progress reports. Includes autonomous execution capability via master prompts and complete documentation templates for third-party QA team handoffs. Implements OWASP security testing and achieves 90% coverage targets.

This skill should be used when setting up, auditing, or enforcing internationalization/localization in UI codebases (React/TS, i18next or similar, JSON locales), including installing/configuring the i18n framework, replacing hard-coded strings, ensuring en-US/zh-CN coverage, mapping error codes to localized messages, and validating key parity, pluralization, and formatting.

Use when the user asks to review pull requests, analyze code changes, check for security issues in PRs, or assess code quality of diffs.