1.1K skills ・ Works with: Google Cloud · sorted by popularity
Turn a plain-language data request into SQL tailored to your database. Build queries that combine tables, filter records, and calculate summaries, with explanations of each step, performance considerations, and suggestions for adjusting dates or other conditions.
Create or improve a company-specific data analysis skill by gathering analysts’ knowledge and examining database structures. Document business terms, metric formulas, table relationships, and common query patterns in reusable reference files.
Write and improve SQL for major data warehouses, accounting for differences in their syntax. Use it to build analytical queries, translate existing SQL, investigate errors, and review slow queries for performance improvements.
Turn repeated workflows into reusable Picoclaw skills, or update and review existing ones. Organize SKILL.md instructions, scripts, reference documents, and output assets, then check the structure and test representative tasks.
Plan a prospective clinical study by ranking endpoints, estimating participant numbers and statistical power, and assessing feasibility. Outputs include assumptions and named reviewers, providing material for expert review before a protocol is finalized.
Automate Google Workspace tasks with the gws command-line tool, including email, file management, spreadsheets, and scheduling. Get guidance on installation, authentication, reusable workflow templates, and security audits of sharing and account settings.
Design and operate shared secret storage with HashiCorp Vault or cloud services. The skill guides access policies, automated credential rotation, temporary credentials, audit analysis, and secret delivery to applications and deployment pipelines.
Design systems that collect, transform, and store data. Choose between scheduled and continuous processing, generate workflow configurations, validate data quality, and analyze performance using guidance for tools including Python, SQL, Spark, Airflow, dbt, and Kafka.
Review cloud permissions, public storage access, network rules, and infrastructure definitions for security gaps. The skill helps identify risky configurations, rank findings by severity, and suggest narrower permissions, with fuller coverage for AWS than Azure or GCP.
Design Google Cloud infrastructure around application needs, scale, and budget. Get service recommendations, cost estimates, infrastructure configuration files, and deployment guidance, with support for automated delivery and security configuration reviews.
Audit environment files and repository contents for possible credential leaks, then prioritize findings by severity. Plan credential replacement, improve configuration examples, and establish checks in development and delivery pipelines to reduce accidental exposure.
Create CI/CD configurations, which automate build, test, and deployment steps, alongside Terraform infrastructure templates and Kubernetes deployment files. Generate health-check and rollback instructions to review before applying changes to cloud infrastructure or application environments.
Helps startup leaders make strategic data decisions: assess permission to train AI on customer data, choose data architecture, evaluate customer data as a business asset, and sequence hiring around the decisions the business needs to make.
Create or update Codex skills that package specialized knowledge, repeatable workflows, and tool instructions. The guide covers concrete use cases, folder structure, reusable resources, starter generation, and basic validation of names and required metadata.
Turn everyday questions into SQL queries, the commands used to retrieve and summarize database records. Uses your database structure and platform to produce queries with explanations, performance notes, and optional validation scripts.
Match Google Cloud data residency and access requirements to available data boundary frameworks and cloud controls. Compare ranked recommendations in a table, see requirement gaps, and receive deployment guidance with built-in frameworks prioritized.
Design and create custom cloud controls and frameworks for Google Cloud data boundary requirements that existing resources cannot meet. Receive prepared configuration fields for manual setup, or approve creation through the agent.
Diagnose GKE TPU node pool creation or expansion failures despite reserved capacity. Trace which virtual machines and unhealthy node pools occupy reservation slots, check automatic repair settings, and provide remediation steps for the user to apply.
Configure authentication and per-project request limits for Google Cloud API Gateway. Secure access to Cloud Run backends, validate quota changes against existing configurations, and investigate HTTP 429 or Service Control Quota errors, including on MCP-enabled gateways.
Diagnose GKE TPU virtual machines that remain in repair by checking instance status, host events, and automatic repair history. Understand the impact on grouped TPU nodes and identify recovery steps for the user to apply.
Assess existing Google Cloud folders and projects through read-only discovery. Compare resource locations, service usage, and customer-managed encryption requirements with Assured Workloads frameworks, then report suitable options and policy readiness findings.
Creates Terraform configuration for Google Cloud Monitoring notification channels, including email, Slack, and Pub/Sub, and attaches channels to existing alert policies. It also checks Pub/Sub topic compatibility and publishing permissions when inspecting the cloud environment.
Expose REST APIs as tools for AI agents through Google Cloud API Gateway using MCP, a protocol for connecting agents to tools. Covers OpenAPI migration, authentication, client connections, validation, and troubleshooting.
Implement Google sign-in for web applications using Google Identity Services. Add sign-in buttons or One Tap, verify ID tokens as proof of identity, configure browser security policies, and handle sessions, sign-out, and account disconnection.