'complexity' 검색 결과

Project onboarding - determine project type, complexity, tech stack, and route to correct phase

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Apply systematic problem-solving techniques when stuck. Use for complexity spirals, innovation blocks, recurring patterns, assumption constraints, simplification cascades, scale uncertainty.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Full codebase health assessment. Use when diagnosing project health or starting a rescue workflow on legacy code — OR when evaluating an external GitHub repo for dependency / fork / contribution decisions (--external mode). Analyzes complexity, dependencies, dead code, tech debt, and git hotspots. Produces a health score and rescue plan.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Zustand state management for React and vanilla JavaScript. Use when creating stores, using selectors, persisting state to localStorage, integrating devtools, or managing global state without Redux complexity. Triggers on zustand, create(), createStore, useStore, persist, devtools, immer middleware.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Algorithms and data structures from first principles through advanced analysis. Covers sorting (bubble, insertion, selection, merge, quick, heap, radix), searching (linear, binary, BFS, DFS, Dijkstra, A*), fundamental data structures (arrays, linked lists, stacks, queues, hash tables, trees, heaps, graphs, tries), complexity analysis (Big-O, Big-Omega, Big-Theta, amortized), recurrence relations, and algorithm design paradigms (divide-and-conquer, greedy, dynamic programming, backtracking). Use when analyzing, selecting, implementing, or comparing algorithms and data structures.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Structured approaches to decisions under uncertainty and complexity. Covers expected value, decision trees, multi-criteria decision analysis, System 1 vs System 2 allocation, pre-mortems, reversible vs irreversible decisions, and the distinction between good decisions and good outcomes. Use when choosing among alternatives with uncertain or multi-dimensional consequences, especially when the stakes justify a deliberate rather than intuitive process.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Systematic code maturity assessment using Trail of Bits' 9-category framework. Analyzes codebase for arithmetic safety, auditing practices, access controls, complexity, decentralization, documentation, MEV risks, low-level code, and testing. Produces professional scorecard with evidence-based ratings and actionable recommendations. (project, gitignored)

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Code refactoring patterns and techniques for improving code quality without changing behavior. Use for cleaning up legacy code, reducing complexity, or improving maintainability.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Lee Cronin's Assembly Theory for molecular complexity measurement and life detection via assembly index computation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ABD quorum-based linearizable registers for distributed storage — the canonical crash-tolerant read/write protocol with precise RTT and message complexity.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when checking skill quality, validating frontmatter before commit, or diagnosing validator warnings. Runs the plugin validator on a skill, agent, or plugin directory — reports token complexity, broken links, frontmatter issues, and structural problems. Pass the path as an argument.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Apply systematic problem-solving techniques for marketing challenges including campaign complexity (simplification cascades), creative blocks (collision-zone thinking), recurring campaign patterns (meta-pattern recognition), assumption constraints (inversion exercise), audience scale uncertainty (scale game), and dispatch when stuck. Techniques derived from proven problem-solving frameworks adapted for marketing execution.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyze code coverage and CRAP (Change Risk Anti-Patterns) scores to identify high-risk code. Use OpenCover format with ReportGenerator for Risk Hotspots showing cyclomatic complexity and untested code paths.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Guidance for selecting appropriate AI model (sonnet vs haiku) based on task complexity, reasoning requirements, and performance needs. Use when implementing agents or justifying model selection.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create new AgentOps skills via interactive interview. Supports from-scratch and clone modes with tiered complexity.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Review changed Anabasis v2 code for reuse, simplification, efficiency and altitude, then apply the fixes. Quality only: it hunts no bugs, which /code-review does. Starts from what the repository already finds (the lint plugins, the whole-tree census, the not-slop ledger), measures before and after with reduce-complexity's scripts, and holds a pass to its budgets and to the rules no pass trades. Use as /simplify on your own diff before a commit, or when the operator asks whether code is simple enough, why something exists, to go one layer higher, or to remove something and find another way.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

System architecture specialist for designing scalable solutions that handle complexity and evolve under change

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Plan and execute your second and third contributions to become a regular contributor. Covers relationship building, progressive complexity escalation, and community presence. Use when your first PR was merged and you want to keep contributing, when transitioning from one-off contributor to regular, or when planning a sustained OSS involvement. Not for your first contribution — use the oss-find-issue → oss-contribute chain for that.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when asked to analyze a file, a directory, or the whole codebase to understand structure, architecture, dependencies, complexity, duplication, dead code, or technical debt — e.g. "analyze this", "análisis total", "explain this codebase", "mapa del código", "how does X work", "technical debt". Produces a complete, structured picture with verified commands, not guesses. Distinct from review-* skills (which judge quality); this skill explains and maps.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Automatically optimize AI agent credit usage by routing tasks to the most cost-efficient execution path. Use when you want to reduce AI API costs by 30-75% without quality loss, classify task complexity before execution, route simple tasks to free or low-cost models, split complex tasks into optimized sub-tasks, or detect vague prompts before wasting credits.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate structured software specifications for features, bug fixes, and products. Use when the user wants to create a spec, PRD, feature brief, requirements document, or when starting any new implementation that needs a specification first. Invoke via /spec-writer or when the user says "write a spec", "spec this out", "create a spec", "I need a spec for...", or describes a feature they want to build. Produces adaptive-complexity specs with Job Stories, Gherkin acceptance criteria, and three-tier boundaries. Output is a markdown file ready for agent execution or human review.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when Codex must make a high-quality judgment on any complex problem, not only technical problems. Trigger when a question has high complexity, uncertainty, cost of being wrong, long-term impact, value tradeoffs, possible structural causes, or when the user asks for 全面思考, 深度理解, 系统性分析, 帮我想清楚, 从根上看, 这件事到底怎么看, 方法论, 复杂问题拆解, 系统方案, 架构判断, 策略判断, or 根因分析. Also trigger for project and engineering high-risk scenarios such as multi-module, multi-environment, multi-data-source, multi-state, financial truth, live trading, ledger, revenue, customer assets, order governance, broker interfaces, online availability, major solution selection, and system closure.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use SonarJS-derived rules in .NET repositories that ship JavaScript or TypeScript frontends and need deeper bug-risk, code-smell, or cognitive-complexity checks than a minimal ESLint baseline. Use when the repo wants `eslint-plugin-sonarjs` locally or already runs SonarQube or SonarCloud in CI.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.