Generate memes using the memegen.link API. Use when users request memes, want to add humor to content, or need visual aids for social media. Supports 100+ popular templates with custom text and styling.

Generate memes using the memegen.link API. Use when users request memes, want to add humor to content, or need visual aids for social media. Supports 100+ popular templates with custom text and styling.

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

When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. For cold outreach emails, see cold-email. For in-app onboarding, see onboarding-cro.

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

Configures Solid Queue for background jobs in Rails 8. Use when setting up background processing, creating background jobs, configuring job queues, or migrating from Sidekiq to Solid Queue.

Generate targeted test inputs to reach specific code paths and hard-to-reach behaviors in Python code. Use when: (1) Targeting uncovered branches or specific execution paths, (2) Need coverage-guided test generation, (3) Want to leverage LLM understanding of code semantics for meaningful test inputs, (4) Testing boundary conditions and edge cases systematically, (5) Combining symbolic reasoning with fuzzing. Provides path analysis, constraint solving, coverage-guided strategies, and LLM-driven semantic generation for comprehensive test input creation.

Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.

Designs distributed system architectures, decomposes monoliths into bounded-context services, recommends communication patterns, and produces service boundary diagrams and resilience strategies. Use when designing distributed systems, decomposing monoliths, or implementing microservices patterns — including service boundaries, DDD, saga patterns, event sourcing, CQRS, service mesh, or distributed tracing.

Upgrade Gamma SDK versions and migrate between API versions. Use when upgrading SDK packages, handling deprecations, or migrating to new API versions. Trigger with phrases like "gamma upgrade", "gamma migration", "gamma new version", "gamma deprecated", "gamma SDK update".

Track large cryptocurrency transactions and whale wallet movements in real-time. Use when tracking large holder movements, exchange flows, or wallet activity. Trigger with phrases like "track whales", "monitor large transfers", "check whale activity", "exchange inflows", or "watch wallet".

Configure this skill should be used when the user asks about "API contract", "api-contract.md", "shared interface", "TypeScript interfaces", "request response schemas", "endpoint design", or needs guidance on designing contracts that coordinate backend and frontend agents. Use when building or modifying API endpoints. Trigger with phrases like 'create API', 'design endpoint', or 'API scaffold'.

This skill enables Claude to optimize machine learning model hyperparameters using grid search, random search, or Bayesian optimization. It is used when the user requests hyperparameter tuning, model optimization, or improvement of model performance. The skill analyzes the current context, generates code for the specified search strategy, handles data validation and errors, and provides performance metrics. Trigger terms include "tune hyperparameters," "optimize model," "grid search," "random search," and "Bayesian optimization."

Use when writing Spark jobs, debugging performance issues, or configuring cluster settings for Apache Spark applications, distributed data processing pipelines, or big data workloads. Invoke to write DataFrame transformations, optimize Spark SQL queries, implement RDD pipelines, tune shuffle operations, configure executor memory, process .parquet files, handle data partitioning, or build structured streaming analytics.

Designs distributed system architectures, decomposes monoliths into bounded-context services, recommends communication patterns, and produces service boundary diagrams and resilience strategies. Use when designing distributed systems, decomposing monoliths, or implementing microservices patterns — including service boundaries, DDD, saga patterns, event sourcing, CQRS, service mesh, or distributed tracing.

Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke to create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, or generate OpenAPI documentation. Trigger terms: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python.

Strategic guide for becoming an effective GitHub contributor. Covers opportunity discovery, project selection, high-quality PR creation, and reputation building. Use when looking to contribute to open-source projects, building GitHub presence, or learning contribution best practices.

AINE (AI-Native SDLC) Reference Architecture advisor. Reviews architecture decisions against AINE principles, recommends AI-native design patterns, guides context engineering maturity progression, and helps teams structure spec-driven workflows. Use when designing AI-native systems, planning software delivery lifecycle improvements, evaluating tooling or foundation model choices, setting up agentic workflows, or when the user mentions AINE, AI-Native SDLC, spec-driven development, context engineering, MCP servers, agentic orchestration, context engineering maturity, or AI-assisted SDLC. Also use when users ask specifically about how AI integrates across product, design, implementation, testing, deployment, and maintenance phases, or want to evaluate AI-native architecture patterns and agent orchestration strategies.

Investigate and resolve Cloudflare configuration issues using API-driven evidence gathering. Use when troubleshooting ERR_TOO_MANY_REDIRECTS, SSL errors, DNS issues, or any Cloudflare-related problems. Focus on systematic investigation using Cloudflare API to examine actual configuration rather than making assumptions.