Skill UI

A deep-dive session designed to stress-test a technical plan against an existing domain model. This process forces the user to resolve ambiguities, sharpen terminology, and validate decisions by cross-referencing code and existing documentation (CONTEXT.md, ADRs). It ensures architectural rigor and completeness before implementation.

A structured methodology for validating non-trivial decisions by subjecting them to an adversarial, fresh-context review. This process is crucial when correctness is paramount—such as in production, security-sensitive logic, or complex architecture—by forcing a skeptical examination that aims to disprove assumptions rather than simply approve them.

This tool simulates a Chief Technology Officer's comprehensive review, stress-testing any major technical plan. It systematically interrogates critical areas including scaling limits (scaling cliffs), accumulated technical debt, team capacity planning, build-vs-buy economics, system reliability (SLOs), and security compliance. Use it before committing to core architecture changes or making high-stakes engineering decisions.

A comprehensive guide detailing the selection criteria for core modern system components, including databases (SQL/NoSQL), caching, message queues, and API protocols. It helps architects choose the optimal technology for specific use cases, scalability needs, and architectural patterns.

This skill generates a comprehensive Technology Radar document following the ThoughtWorks format. It provides a structured framework for an engineering team to evaluate and categorize all significant technologies (tools, languages, platforms, techniques) into four quadrants (Adopt, Trial, Assess, Hold). It helps establish a shared, explicit technology strategy, detailing adoption rationales, decision trails, and maintenance processes for consistent engineering choices.

A comprehensive skill for systematically building, refining, and documenting a project's domain model. It helps define core terminology, establish a ubiquitous language, and record critical architectural decisions (ADRs). Use this when you need to challenge ambiguous language, invent edge-case scenarios, or maintain architectural consistency throughout the development lifecycle.

This skill helps developers structure and record critical architectural decisions (ADRs) made during coding sessions. It automatically detects moments of decision, capturing the context, alternatives considered, and the rationale (trade-offs and consequences). This maintains a living log that explains 'why' the code base was built the way it is, preventing knowledge loss and improving project maintainability.

This guide outlines the critical rules for structuring technical research papers submitted to top-tier conferences like ASE. It emphasizes the 'decision-criticality' rule, instructing authors on how to separate core arguments (which must fit within the 10-page body) from reproduction details, raw logs, and supplementary material (the artifact). Mastering this separation is crucial for ensuring reviewers judge the paper on its merits, not its supplementary data.

This guide helps researchers determine if their theoretical computer science result is suitable for ICALP, the premier European conference. It details the crucial two-step decision process: first, selecting the correct venue (ICALP vs. STOC/FOCS/SODA/Journals), and second, classifying the work into the appropriate specialized track (Track A: Algorithms, or Track B: Logic, Automata, and Semantics).

This guide provides a rigorous, step-by-step framework for authors responding to major journal critiques, such as those received after a JAMA revision decision. It emphasizes maintaining scientific integrity by structuring point-by-point replies, accurately citing revisions, and addressing statistical and methodological concerns without fabricating new findings or overstating results.

This guide provides detailed instructions on writing the policy implications section for manuscripts submitted to quantitative journals (like JQTE). It emphasizes grounding all policy recommendations in the paper's specific quantitative findings (measurement, forecasting, or decomposition results), ensuring the advice is actionable, timely, and relevant to planning, industry, and technology decisions.

A comprehensive methodological guide for researchers submitting data management papers. It helps users assess if their contribution is a fundamental system advance or merely an application. The guide provides detailed decision frameworks and comparisons between top-tier venues like SIGMOD, PVLDB, KDD, and PODS, ensuring the focus remains on the core data-management primitive.