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Build or review Django applications using examples for project structure, APIs, database access, and caching. Apply patterns for separating settings and business logic, validating requests, and reducing repeated database queries.
Plan database schema and data changes for production systems. Use staged column replacements, concurrent index creation, and batched data updates to limit disruption, with migration workflows for PostgreSQL, Prisma, Drizzle, Kysely, Django, and golang-migrate.
Coordinate parallel frontend, backend, or service development around one shared, machine-checkable interface specification. Generate consumer types, validate mocks and real responses against the same specification, and review changes together to prevent mismatched fields and incompatible integrations.
Prevent token balances and values from being scaled incorrectly across EVM blockchains. Look up each token's decimal places at runtime, cache them by chain and address, and use precise arithmetic with consistent units.
Write or review Dart and Flutter apps with practical patterns for state management, navigation, networking, error handling, and tests. Use code examples to handle missing values, organize widgets, and connect login status to routing.
Write, review, and refactor modern C++ using the C++ Core Guidelines. Covers type safety, automatic resource cleanup, class design, exceptions, concurrency, and naming conventions, with examples and a checklist for identifying unsafe or inconsistent code.
Design and review error handling in TypeScript, Python, and Go applications. Use structured error types, controlled retries, API error responses, and readable failure messages to make failures visible and separate user guidance from developer diagnostics.
Find the ECC command sequence for a development task, including the order to run commands and when to stop. It reads current command files, groups related workflows, and provides guidance without executing them.
Write, review, and refactor C# and .NET code using practical conventions for asynchronous work, configuration, and dependency injection—passing services into classes. Includes examples for data access and APIs to support maintainable applications.
Look up current library and framework documentation through Context7 MCP, a connection to live documentation tools. Supports setup questions, API references, and code examples, using version-specific sources when available to ground answers in retrieved material.
Add background jobs to Django with Celery, moving work such as email delivery and PDF generation outside web requests. Covers scheduled runs, retries, linked or parallel tasks, monitoring, and tests, with Redis or RabbitMQ carrying task messages.
Coordinate parallel AI agent sessions with dmux, a tool that manages terminal panes. Split development, research, testing, or review into separate tasks, isolate overlapping file changes, and review results before merging them.
Review a feature or proposal from four perspectives: product management, architecture, development, and quality assurance. Get each role’s concerns and first actions, followed by a summary of shared priorities and unresolved disagreements.
Investigate unreliable AI agents across 12 layers, including instructions, memory, tool execution, and display. Use code and logs to trace failures, rank findings by severity, and produce an ordered repair plan that prioritizes code changes.
Turn a large engineering objective into a written plan with steps sized for individual pull requests, or proposed code changes. Each step includes context, dependencies, checks, and completion criteria so another agent can continue the work.
Record software design decisions as numbered Markdown files, with context, rejected alternatives, benefits, drawbacks, and risks. Maintain an index and consult existing ADRs—architecture decision records—to explain why a framework, database, or design approach was chosen.
Build shared interfaces for Android, iOS, Desktop, and Web with Compose. This skill guides screen state, navigation, reusable components, themes, and rendering performance, including ways to handle interface differences between platforms.
Use Bun to run JavaScript and TypeScript, manage project dependencies, build applications, and run tests. Includes guidance for choosing between Bun and Node, migrating existing projects, and configuring deployments on Vercel.
Integrate x402, an HTTP payment protocol, so agents can pay for APIs or services. Configure task and session budgets, approved recipients, and wallets with privately managed keys, using integration paths for Base, X Layer, or Solana.
Explore an unfamiliar codebase and turn its structure, request flow, and development conventions into a concise onboarding guide. Create or update CLAUDE.md with project-specific instructions, preserving existing guidance and identifying findings that remain uncertain.
Review and refine code using shared conventions for clear names, readability, error handling, and updates that preserve original data. Identify duplication, oversized functions, and unnecessary complexity to make code easier to understand and maintain.
Organize engineering work carried out by AI agents with clear completion criteria, small verifiable tasks, and evaluations before and after implementation. Match model choice to task complexity and track tokens, retries, time, and outcomes to manage cost.
Plan autonomous Claude Code workflows, from sequential development steps to parallel agents working from a specification. The material explains how to preserve progress between runs, check quality, coordinate merges, and set limits that stop repeated execution.
Structure Android and Kotlin Multiplatform projects with clear boundaries between business logic, screens, and data access. Provides examples for module dependencies, business operations, repositories that coordinate data sources, database integration, and error handling.