
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
Interactive installer for Everything Claude Code — guides users through selecting and installing skills and rules to user-level or project-level directories, verifies paths, and optionally optimizes installed files.
Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.
Use only when writing/updating/fixing C++ tests, configuring GoogleTest/CTest, diagnosing failing or flaky tests, or adding coverage/sanitizers.
Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Django, TypeORM, golang-migrate).
Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications.
Verification loop for Django projects: migrations, linting, tests with coverage, security scans, and deployment readiness checks before release or PR.
Playwright E2E testing patterns, Page Object Model, configuration, CI/CD integration, artifact management, and flaky test strategies.
Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles
FastAPI architecture patterns, async SQLAlchemy ORM, Pydantic schemas, dependency injection, service layer, background tasks, and production-grade API design.
Firebase Authentication patterns — token verification in FastAPI, custom claims for RBAC, multi-tenant auth, ID token validation, service account setup, and frontend Firebase SDK integration.
Apple FoundationModels framework for on-device LLM — text generation, guided generation with @Generable, tool calling, and snapshot streaming in iOS 26+.
GCP serverless deployment patterns — Cloud Run, Cloud Tasks, Secret Manager, Artifact Registry, Cloud Storage, IAM, and cost-aware architecture for production Python services.
Pattern for progressively refining context retrieval to solve the subagent context problem
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot.
iOS 26 Liquid Glass design system — dynamic glass material with blur, reflection, and interactive morphing for SwiftUI, UIKit, and WidgetKit.
Process, convert, OCR, extract, redact, sign, and fill documents using the Nutrient DWS API. Works with PDFs, DOCX, XLSX, PPTX, HTML, and images.
Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.
RAG architecture patterns — document ingestion, chunking strategies, embedding models, vector stores, hybrid retrieval, re-ranking, advanced techniques (HyDE, multi-query), and evaluation with RAGAS.
Use this skill when adding authentication, handling user input, working with secrets, creating API endpoints, or implementing payment/sensitive features. Provides comprehensive security checklist and patterns.
Use when auditing Claude skills and commands for quality. Supports Quick Scan (changed skills only) and Full Stocktake modes with sequential subagent batch evaluation.
Verification loop for Spring Boot projects: build, static analysis, tests with coverage, security scans, and diff review before release or PR.
Use this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.
A comprehensive verification system for Claude Code sessions.
REST API design patterns including resource naming, status codes, pagination, filtering, error responses, versioning, and rate limiting for production APIs.
Draft cold emails, warm intro blurbs, follow-ups, update emails, and investor communications for fundraising. Use when the user wants outreach to angels, VCs, strategic investors, or accelerators and needs concise, personalized, investor-facing messaging.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
Engineering operating model for teams where AI agents generate a large share of implementation output.
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.
Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.
C++ coding standards based on the C++ Core Guidelines (isocpp.github.io). Use when writing, reviewing, or refactoring C++ code to enforce modern, safe, and idiomatic practices.
Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps.
Django security best practices, authentication, authorization, CSRF protection, SQL injection prevention, XSS prevention, and secure deployment configurations.
Django testing strategies with pytest-django, TDD methodology, factory_boy, mocking, coverage, and testing Django REST Framework APIs.
Docker and Docker Compose patterns for local development, container security, networking, volume strategies, and multi-service orchestration.
Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.
FastAPI security best practices — JWT authentication with python-jose, OAuth2, role-based access, CORS, rate limiting, security headers, and input validation.
FastAPI testing with TDD — pytest-asyncio, httpx AsyncClient, async SQLAlchemy fixtures, polyfactory, mocking external services, and coverage targets.
Frontend development patterns for React, Next.js, state management, performance optimization, and UI best practices.
Create stunning, animation-rich HTML presentations from scratch or by converting PowerPoint files. Use when the user wants to build a presentation, convert a PPT/PPTX to web, or create slides for a talk/pitch. Helps non-designers discover their aesthetic through visual exploration rather than abstract choices.
Idiomatic Go patterns, best practices, and conventions for building robust, efficient, and maintainable Go applications.
Go testing patterns including table-driven tests, subtests, benchmarks, fuzzing, and test coverage. Follows TDD methodology with idiomatic Go practices.
Create and update pitch decks, one-pagers, investor memos, accelerator applications, financial models, and fundraising materials. Use when the user needs investor-facing documents, projections, use-of-funds tables, milestone plans, or materials that must stay internally consistent across multiple fundraising assets.
Java coding standards for Spring Boot services: naming, immutability, Optional usage, streams, exceptions, generics, and project layout.
Kubernetes production patterns — Deployments, Services, Ingress, ConfigMaps, Secrets, RBAC, HPA, health probes, resource limits, and Helm chart structure for containerized Python/Node services.
MCP (Model Context Protocol) server patterns — FastMCP server design, tool/resource/prompt definitions, authentication, testing, and deployment.
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
Example project-specific skill template based on a real production application.
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements.
RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.
Decision framework for choosing between regex and LLM when parsing structured text — start with regex, add LLM only for low-confidence edge cases.
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.
Spring Security best practices for authn/authz, validation, CSRF, secrets, headers, rate limiting, and dependency security in Java Spring Boot services.
Test-driven development for Spring Boot using JUnit 5, Mockito, MockMvc, Testcontainers, and JaCoCo. Use when adding features, fixing bugs, or refactoring.
Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
Protocol-based dependency injection for testable Swift code — mock file system, network, and external APIs using focused protocols and Swift Testing.
SwiftUI architecture patterns, state management with @Observable, view composition, navigation, performance optimization, and modern iOS/macOS UI best practices.
Translate visa application documents (images) to English and create a bilingual PDF with original and translation
Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions.
Operate and extend NanoClaw v2, ECC's zero-dependency session-aware REPL built on claude -p.
Thread-safe data persistence in Swift using actors — in-memory cache with file-backed storage, eliminating data races by design.
Patterns and architectures for autonomous Claude Code loops — from simple sequential pipelines to RFC-driven multi-agent DAG systems.
Verification loop for FastAPI projects: Alembic migration checks, linting, async tests with coverage, security scans, and deployment readiness before release or PR.
Intercom integration patterns — webhook event handling, Conversations API, Contacts API, custom inbox channels, operator bot flows, and multi-tenant workspace management.
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
Multi-tenant SaaS patterns — tenant isolation strategies, row-level security, tenant-aware SQLAlchemy models, RBAC, subdomain routing, and Alembic migrations for shared schema.
LLM engineering patterns — prompt design, structured outputs with instructor, tool use, context management, model selection/routing, cost optimization, streaming, retry logic, and observability.
Cache expensive file processing results using SHA-256 content hashes — path-independent, auto-invalidating, with service layer separation.
LLM observability with Langfuse — tracing LLM calls, spans, prompt versioning, cost tracking, evaluation datasets, and multi-tenant trace isolation in FastAPI/Python applications.
Swift 6.2 Approachable Concurrency — single-threaded by default, @concurrent for explicit background offloading, isolated conformances for main actor types.
Scan your Claude Code configuration (.claude/ directory) for security vulnerabilities, misconfigurations, and injection risks using AgentShield. Checks CLAUDE.md, settings.json, MCP servers, hooks, and agent definitions.
CUDA kernel development and GPU optimization patterns — memory hierarchy, occupancy tuning, coalescing, shared memory tiling, warp-level ops, and profiling with Nsight Compute. Use when writing or optimizing CUDA C++ kernels.
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
Research-before-coding workflow. Search for existing tools, libraries, and patterns before writing custom code. Invokes the researcher agent.