Skill UI

This guide enforces the 'spec-first' principle in software development, treating the specification as a non-negotiable contract. It outlines a rigorous, multi-stage workflow detailing mandatory sections (Functional/Non-Functional Requirements, Acceptance Criteria, API Contracts, Data Models) and bounded autonomy rules. Users learn how to define the system 'must do' before writing a single line of code, thereby minimizing rework and eliminating scope creep.

Keeps project-specific memory for Claude Code by auto-loading context on each session, tracking git activity, and running deterministic Node.js scripts so instructions remain consistent across models.

A library-agnostic Flutter/Dart code review checklist that walks through widget best practices, state management patterns, Dart idioms, performance, accessibility, security, and clean architecture, helping reviewers spot regressions in any app stack.

Transforms Claude Code into a continuous autonomous agent with persistent memory, scheduled operations, remote dispatch, computer automation, and task queuing for repeatable workflows and monitoring.

Extracts business domain knowledge from a codebase, optionally reusing an existing knowledge graph, and generates an interactive horizontal flow graph for dashboard visualization, with lightweight scanning and validation steps.

A comprehensive guide to structuring Flutter applications using a feature-first, layered architecture. It defines clear separation of concerns across UI, Logic (Domain), and Data layers, ensuring maintainability and testability. This approach guides developers on organizing code by feature modules, making it ideal for building complex, scalable, and long-lived applications while remaining agnostic to specific state management solutions.

This tool compresses natural language memory files (e.g., notes, todos, preferences) into a highly condensed, 'caveman-speak' format. It significantly reduces input tokens by systematically removing articles, filler words, and redundant phrasing. Crucially, it intelligently preserves all technical substance, including code blocks, URLs, file paths, and structured markdown elements, ensuring data integrity while maximizing efficiency for LLM interactions.

This skill provides comprehensive guidance for setting up production-grade Continuous Integration/Continuous Deployment (CI/CD) pipelines for Go projects using GitHub Actions. It covers all critical stages, including rigorous unit testing with race detection, advanced linting, static application security testing (SAST) via tools like CodeQL and govulncheck, automated dependency management (Dependabot/Renovate), container image building, and automated binary release using GoReleaser. Use this when building a robust quality gate for a Go codebase.

This guide provides comprehensive best practices for Go code quality using the industry-standard `golangci-lint` tool. It covers the full development workflow, including initial setup and configuration of `.golangci.yml`, running linters (like govet, staticcheck), automatically fixing issues, correctly suppressing warnings using `//nolint` directives, and interpreting complex linter output to ensure high code maintainability and security.

This comprehensive guide provides best practices for structuring and initializing Golang projects. It covers standard layouts for various project types (CLI tools, microservices, libraries, monorepos), adhering to 12-Factor App principles, and mastering Go module naming conventions. Use this resource when starting a new Go project or refactoring an existing codebase to ensure scalability, maintainability, and architectural soundness.

Adds samber/oops structured error builders to Go services, giving stack traces, codes, user-friendly messages, panic recovery, and exporter-friendly attributes for observability and diagnostics.

This mode simulates a P9 Tech Lead role, specializing in strategic project management and complex task orchestration. It does not write code itself, but focuses on generating detailed, structured Task Prompts (six elements) and managing the entire workflow delivery from multiple specialized agents (P8 teams). Ideal for coordinating large, complex projects requiring strategic decomposition and coordination of three or more parallel agents.