Search Skills

Monitors real-time trends across Reddit, Instagram, and TikTok to generate actionable market insights and content strategy recommendations.

Analyzes website SEO health by evaluating page elements, technical metrics, and content quality to generate actionable optimization reports for improved search rankings.

Optimizes article structure for AI models (e.g., ChatGPT, Claude) to ensure Google indexing and AI citation readiness.

Analyzes YouTube video transcripts to generate structured summaries, core points, and key concepts for efficient content comprehension.

Automates competitor data collection including company profiles, pricing, and user reviews to generate structured market analysis reports.

Automates AI-generated short video creation and cross-platform publishing to YouTube, TikTok, Instagram, and other social media.

Creates AI-generated viral social media posts with custom images and automates publishing to Facebook/Instagram via browser automation.

Configures GitHub repositories with integrations, GitHub Actions for agent invocation, and Claude/Codex skill localization procedures.

Enables complex ontology querying and management using the Ontology Access Kit (OAK) for semantic data integration and knowledge graph applications.

Guides consistent ontology term creation and maintenance using Dead Simple Ontology Design Patterns for structured data modeling.

Provides cross-platform file operation utilities to ensure consistent behavior on macOS, Windows, and Linux systems.

Builds MCP servers on Cloudflare Workers with OAuth, Durable Objects, and WebSocket hibernation for AI model context management.

Generates structured project planning documentation including phases, verification criteria, and conditional technical artifacts for web development projects.

Configures serverless Postgres databases (Neon/Vercel) for Cloudflare Workers with connection pooling, branch management, and ORM integration.

Provides tools for building backend AI applications with Vercel AI SDK v5/v6, including migration, error handling, and latest model integration.

Systematically quantifies and manages technical debt using SQALE methodology with objective prioritization and prevention strategies for code maintainability.

Optimizes CI/CD pipelines with quality gates, release automation, and observability to reduce build times and prevent production failures.

Provides structured onboarding with time-boxed learning paths (Day-1, Week-1, Month-1) to accelerate contributor ramp-up and systematize knowledge transfer.

Establishes a quality baseline (V_meta ≥0.40) in iteration 0 to reduce project iterations by 40-50% via strategic planning and historical data analysis.

Systematic methodology for creating compact, expressive prompts for Claude Code subagents using lambda contracts and symbolic logic, validated for agent composition and tool integration.

Provides a BAIME-aligned refactoring protocol for Go code in CLIs, services, and MCP tooling with automated metrics and documentation.

Provides systematic error handling methodology with taxonomy, diagnostics, recovery patterns, and prevention guidelines for software error reduction.

Validates methodology effectiveness through historical data analysis with statistical confidence, avoiding live deployment to reduce time and cost.

Systematic Go testing methodology using TDD, fixture patterns, and coverage-driven gap closure to improve test coverage and speed.