923 skills · sorted by relevance
Turn a multi-step plan into ready-to-paste ECC slash commands, text commands entered with a slash. Each generated command includes its step identifier, task scope, and acceptance criteria. Steps that cannot carry their scope are marked as blocked for manual handling.
Write, review, and refactor Kotlin code using established conventions. Covers safe handling of missing values, immutable data, coroutines for asynchronous work, and type-safe configuration builders, helping keep application code readable and maintainable.
Coordinate feature work, bug fixes, refactoring, and MVP development through shared phases scaled to the change. Related operation skills use this workflow to delegate research, planning, test-first implementation, review, and commits with human approval checkpoints.
Design or refactor services so business rules stay separate from databases, APIs, and frameworks. Uses Ports and Adapters—interfaces and their implementations—to define clear boundaries, test workflows, and migrate existing code one feature at a time.
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.
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.
Guide development through test-driven development (TDD): write a test, confirm it fails, add minimal code, then clean up. Apply this cycle to features and bug fixes while checking that existing behavior still passes its tests.
Coordinate large migrations, reviews, or research tasks across multiple agents. Keep plans and intermediate results in scripts and files, challenge findings with independent checks, and integrate verified work in controlled batches.
Guide coding tasks toward the smallest complete change by reusing existing code, platform features, and installed dependencies. Address affected callers and necessary checks, then explain skipped work, unchecked areas, and risks in a brief reply.
Restructure code through extraction, consolidation, or responsibility moves while preserving its behavior. Establish checks before editing, repeat them afterward, and keep intermediate versions buildable and testable without mixing in feature changes.
Connect agent tasks into a sequence where each step receives the previous output. Use custom prompts or predefined workflows to analyze code, plan refactoring, generate tests, optimize performance, or transform data through multiple stages.
Work with AI as a coding partner, choosing who writes code and who guides the work. Supports role switching, test generation, ongoing code review, debugging, and step-by-step explanations for learning.
Audit a codebase for unnecessary complexity, including dead code, duplicated state, redundant interfaces, and obsolete compatibility paths. Receive evidence-backed simplification candidates, or authorize changes that remove justified targets and validate the behavior that must remain.
Simplify Rust code in RTK by replacing verbose loops, unnecessary copies, and excessive abstractions with common Rust patterns. Preserve behavior and project requirements, including error context, fallback handling, exit codes, and existing test modules.
Guide Rust development through test-driven development: write a failing test, implement enough code to pass, then refactor. Includes practical test patterns and final checks for formatting, static analysis, and test results.
Choose Rust design patterns for RTK modules that process command output. Use concrete examples to structure configuration, prevent type mixups, manage parser states, and select abstractions suited to the task without adding unnecessary architectural complexity.
Keep coding changes small by questioning unnecessary work and reusing existing code, standard libraries, and native platform features. Apply this approach to implementation, bug fixes, reviews, and dependency choices while preserving validation, security, and accessibility.
Breaks complex goals into actionable tasks, plans their order, and coordinates execution across agents. It tracks progress, adjusts priorities and dependencies, and combines separate outputs into a consistent deliverable.
Assembles teams of AI agents by analyzing task complexity, required skills, and resource needs. It covers selecting specialists, adjusting team size to workload, and refining coordination using patterns from past executions.
Turn specifications and designs into working code using test-driven development: write failing tests, implement enough code to pass, then refactor. The workflow also covers error handling, performance improvements, documentation, and coordinated changes across components.
Coordinate groups of AI agents across multiple GitHub repositories. Analyze dependencies, organize shared updates and refactoring, run tests, and create linked pull requests so related projects can be changed together.
Set up a coordinated team of three or more AI agents for development tasks spanning multiple files. Configure the team structure, assign specialized roles, and prepare parallel work with named agents and messaging.
Coordinate changes across multiple GitHub repositories, align package versions, synchronize documentation, and run integration tests. The skill also guides shared repository templates and organizes AI agents to handle related development tasks.
Organize software development from requirements and design through testing, review, and deployment. Uses Claude Flow to coordinate specialized agents, share decisions across sessions, and guide implementation with tests written before code.