Coding standards, frameworks, refactoring, and code review (15.8K skills)
Investigate a Homecore capability by tracing relevant source files, tests, and accepted architecture decisions. Check documented status and limitations before proposing code, while keeping implementation presence separate from deployment compatibility or claims of Home Assistant parity.
Set up an ESP32-S3/C6 sensing node for RuView by choosing firmware, checking and flashing binaries, and configuring WiFi and capture settings. Use boot logs to confirm CSI, measurements of the WiFi channel, is being captured.
Review GitHub pull requests, or proposed code changes, with specialized agents covering security, performance, architecture, and style. Generate actionable comments, apply quality thresholds, and coordinate automated review workflows.
Start using RuView by choosing a Docker demo, a source build, or a live ESP32 setup. The skill guides the next concrete step, distinguishing sample data playback from sensing an actual room with WiFi signals.
Connect RuView sensing data to AI agents through tools for presence, breathing, and heart rate. Explore agent coordination and prototype storing agent state and decisions alongside sensing data in a shared RVF container.
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.
Restructure claude-flow v3 into focused modules using Domain-Driven Design, which groups code by responsibility. Define module boundaries, event communication, and plugin interfaces to support a modular architecture with independently testable business logic.
Set up RuView sensing nodes by building and flashing ESP32 firmware, configuring WiFi and the receiving address, and checking serial logs. Diagnose missing CSI streams, the WiFi signal measurements sent by sensing nodes.
Modernize the claude-flow v3 command-line interface by splitting large command files, adding interactive prompts, connecting hooks that run on execution events, and organizing multiple commands into automated workflows with progress reporting.
Set up radar sensing for contactless heart rate, breathing rate, presence, and distance measurements. It covers supported hardware, firmware, and combining radar with WiFi CSI, sensing data derived from wireless signals, for shared readings and 3D views.
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.
Integrate RuView through shell commands, an HTTP API, or WebAssembly builds, which run compiled code in browsers and supported edge devices. Covers survivor scan commands, result exports, API hosting, and browser or ESP32 deployment paths.
Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.
Get RuView running with a Docker demo using simulated WiFi signal data, source checks, or live sensing with supported hardware. Choose a starting path based on available equipment and open a working sensing dashboard.
Improve the MCP server that connects claude-flow v3 to tools. It guides connection reuse, faster tool lookup, request distribution, and communication changes, with monitoring to evaluate response times, errors, memory use, and cache performance.
Refactor claude-flow into an extension of agentic-flow@alpha to reduce duplicate implementations. Plan adapter layers, migrate agent and task management, and connect learning, shared memory, and tools while checking compatibility with existing functionality.
Automate checks, code formatting, agent coordination, and session records around Claude Code operations. Uses hooks, actions triggered before or after work, to preserve context and connect development tasks with shared memory.
Implement core TypeScript modules for claude-flow v3 using domain-driven design, which organizes code around distinct responsibilities. Build task and session domains, connect storage and services, and add unit and integration tests.
Find official documentation for a library, framework, or API and apply it to the task at hand. Check the relevant version, distinguish documented facts from assumptions, and verify code changes with a focused test or concrete command.
Diagnose failed, timed-out, or incomplete terminal commands using command output and environment checks. The skill guides targeted retries, avoids duplicate long-running jobs, and verifies that the intended files, processes, or service state were produced.
Find reusable UI components in Storybook, create or update stories that show their states, run story tests, and publish a curated review so others can inspect the results of UI changes.
Look up a project's existing UI components in Storybook, including their props, or configuration inputs, and usage examples. Use the findings to answer questions and identify components to reuse before building duplicates.
Create a draft pull request from the current branch using the project’s template. The skill checks changes, detects the base branch, gathers label choices, and prepares a title, description, and testing details.
Add Storybook to a project that does not have it configured, choosing the installation tag based on the latest stable version. Then use the separate setup skill to configure Storybook for the project.