Skill UI

This guide provides best practices for technical documentation, emphasizing the capture of context (the *why*) rather than just code (the *what*). It details how to write Architecture Decision Records (ADRs) for significant architectural choices, such as database selection, API design, and framework choice. Utilizing ADRs ensures that future engineers and teams understand the original reasoning, constraints, and trade-offs made during development.

This guide provides comprehensive solutions for common Flutter runtime and layout errors, such as RenderFlex overflow, unbounded constraints, and improper state management (setState during build). It explains the cause, the specific error message, and provides actionable code fixes for various UI and state issues.

This library provides powerful monadic types, including Option, Result, and Either, for Go. It enhances type safety by replacing manual nil checks with type constraints and transforming verbose error handling into composable pipelines. It is essential for adopting modern functional programming patterns and building robust, resilient Go applications.

Interactive workflow that interrogates scope, deliverables, constraints, and success criteria while guiding users to refine task prompts; copies the final markdown with Joyride clipboard commands and never writes code.

Creates a machine-readable specification template tailored for Generative AI solutions, covering purpose, requirements, constraints, interfaces, dependencies, and validation so implementation stays unambiguous.

Interactive workflow that uses the joyride_request_human_input tool to probe scope, deliverables, and constraints before executing any task, ensuring thorough clarification and structured planning.

This technique guides users on decomposing multi-constraint questions, especially in the domain of football trivia or historical research. Instead of searching all criteria simultaneously, it instructs users to rank constraints by distinctiveness (e.g., specific match results first, then historical milestones). By performing incremental, cascading searches, the system dramatically narrows down the result set, leading to more accurate information retrieval.

This skill guides the systematic process of identifying and verifying candidate football entities (players or clubs). Use it when initial search results suggest a lead, or when the question provides enough detailed constraints (e.g., nationality, era, league) to hypothesize a candidate. The technique involves constructing targeted name-based searches and cross-checking every constraint (birth year, career timeline, etc.) against the found profile to ensure accuracy.

A structured methodology for precisely identifying specific geographic locations or historical landmarks. This technique systematically narrows the search scope, moving from broad regions (countries/former states) down through administrative divisions, city centers, and finally to specific monuments or structures. It requires utilizing diverse clues like historical events, census data, and distance constraints, while critically verifying assumptions at each step to ensure accuracy.

This skill enhances research query formulation by translating vague, colloquial, or generalized descriptions into precise, standard academic terminology. When initial search terms are broad (e.g., "conjugal happiness"), this technique suggests multiple plausible academic synonyms (e.g., "marital satisfaction," "relationship quality"). By improving the precision of the search query and incorporating structured constraints (like keywords, years, or sample sizes), it significantly boosts the relevance and effectiveness of academic paper retrieval.

This advanced research technique is designed for deep dives into football topics. Instead of relying solely on the original query, it mandates tracking every discovered entity—such as player names, club names, or coaches—from search results. By treating these entities as new leads, the user must formulate follow-up searches using the discovered names and remaining constraints, ensuring nothing relevant is overlooked and building a comprehensive knowledge chain.

This guide teaches targeted verification strategies for historical research. When initial searches suggest a candidate name or figure, do not continue with broad searches. Instead, immediately switch to verifying the candidate against all specific constraints (time period, location, family details, major events) using precise search queries to confirm identity and eliminate false positives.