Claude Skills by tensology

Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources, or leverage BigQuery's built-in ML capabilities. Also use when performing data analysis, ingesting data into BigQuery, or developing AI applications on BigQuery.

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

CEO/founder-mode scope review. Challenges the scope of any plan, workflow, or feature before execution. Four modes: SCOPE EXPANSION (dream bigger), SELECTIVE EXPANSION (cherry-pick worthwhile expansions), HOLD SCOPE (maximum rigor within current scope), SCOPE REDUCTION (strip to essentials). Use before executing any multi-step workflow or when questioning whether the scope is right. Prevents scope creep and missed opportunities. Use proactively when the user defines a plan, creates a workflow...

Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).

This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for re...

Use when designing or improving a module interface, choosing a seam, reducing shallow modules, making code easier to test, or reviewing architecture for locality, leverage, adapters, and deep-module design.

Use with DecisionsAI when a ticket or workflow needs internet research — social posts, articles, video subtitles, GitHub, RSS, or competitor scans. Routes through Agent Reach upstream tools; run agent-reach doctor first.

Index of DecisionsAI browser automation — Playwright, browser-use, browser-qa, and workflow integration across Codex, Cursor, Claude, and Pi.

Use Composio Connect MCP (Tool Router) for authenticated SaaS actions — Gmail, Slack, Notion, Jira, Linear, GitHub, and 1000+ other apps. Rube is deprecated; do not use it.

Pick a design aesthetic from awesome-design-skills — bundled minimal/professional/enterprise/shadcn/bento; full catalog in reference for on-demand load.

Playbook for Aceternity UI, Refero MCP, Mobbin MCP, and Godly when building or polishing web UI — what each source is for and how agents should use it.

Use when preparing hardest high-leverage work for a stronger or scarce model, building a ranked execution queue, asking for fable prep, frontier prep, round-collapse, wave queue, or model-upgrade readiness across code, design, copy, marketing, or architecture work.

Use when auditing DecisionsAI, Codex, Claude, Cursor, Gemini, Pi, Cline, RTK, workflow pre_chain skills, hooks, projected commands, skill routing, or harness setup for drift, duplication, dead references, slow hooks, bloated context, or stale config.

Use after a verified Decisions harness audit when the user asks to apply safe fixes to harness drift, dead references, stale projected skills, duplicate routing, bloated state files, or invalid local config.

Master index for DecisionsAI harness setup — ECC, Ponytail, Fallow, RTK, browser/content skills, and IDE thread tools.

Index for Corey Haines marketing skills — use product-marketing first, then pull other skills from the reference clone without duplicating all 44 into the harness.

Use Mermaid diagrams in DecisionsAI to explain technical topics — architecture, flows, sequences, and data models via the freestanding diagram viewer.

Research and normalize MotionSites-style prompt directions, then output a clean motion prompt brief for implementation.

Use Open Design for agent-native UI prototypes, decks, motion, and hand-drawn diagrams — complementary to Decisions Mermaid viewer for technical charts.

Use Playwright inside DecisionsAI — Hermes playwright_browser tool, workflow playwright steps, and local Chromium from bin/setup.py.

Run before implementing UI — research real product patterns (Refero/Mobbin MCP), pick a design direction, and output tokens or a short DESIGN.md before writing code.

Route technical planning and review between Decisions Mermaid viewer, BuilderIO visual-plan/recap skills, and Open Design when the work needs richer artifacts.

Use yt-dlp for YouTube (and supported sites) metadata, subtitles, and search inside Decisions workflows — not for Bilibili (use bili-cli via agent-reach).

Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.

Use when a project needs shared terminology, glossary updates, ADRs, clearer domain language, or when user language conflicts with existing code, ticket, board, project, workflow, or CONTEXT.md terms.

Use when you have a written implementation plan to execute in a separate session with review checkpoints

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

Use this skill whenever you are working on a project that uses Firebase products or services, especially for mobile or web apps.

Manages custom Agent resources on Gemini Enterprise Agent Platform. Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations.

Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.

Guides the usage of Gemini Interactions API on Gemini Enterprise Agent Platform. Use when the user wants to use the stateful, server-managed Interactions API for multi-turn conversations, background execution, streaming, structured output, and function calling on the Agent Platform.

Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inferenc...

Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs, NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics.

Provides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.

Guidance for a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource.

Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.

Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident management.

Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.

Generates reliability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use this skill to evaluate a workload, identify reliability requirements, and provide actionable recommendations for build, deploy, and manage the workload reliably in Google Cloud.

Generates security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security.

Generates sustainability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify environmental impact requirements, and provide actionable recommendations to build, deploy, and manage the workload sustainably in Google Cloud.

Persistent cross-session knowledge base. Manages per-project learnings that compound across sessions — patterns, pitfalls, preferences, and project quirks. The agent gets smarter on your codebase over time. At session start, searches relevant learnings. During sessions, logs discoveries. Supports review, search, prune, and export. Use proactively when the agent encounters a durable project quirk, user preference, or pattern that would save 5+ minutes next time. Also use at session start to re...

Creates 5 root documentation files (PROJECT.md, docs/README.md, documentation_standards.md, principles.md, tools_config.md).

Creates 4 core project docs (requirements.md, architecture.md, tech_stack.md, patterns_catalog.md). ALWAYS created.

Creates reference documentation structure + smart documents (ADRs/Guides/Manuals) based on TECH_STACK. Only creates justified documents (nontrivial technology choices).

Creates test documentation (testing-strategy.md + tests/README.md). Establishes testing philosophy and Story-Level Test Task Pattern.

Builds interactive HTML presentation with 6 tabs (Overview, Requirements, Architecture/C4, Tech Spec, Roadmap, Guides). Creates presentation/README.md hub.

Creates .pi/skills from procedural doc sections with proper structure and transformation

Universal skill reviewer: SKILL mode (D1-D9 + M1-M5) or COMMAND mode (skill review)