'consistency' 검색 결과

Use when 高教社杯/CUMCM 数学建模论文、摘要、正文、表图、附录、登记表、结论、数值、单位、场景标签、可行性措辞或提交包需要跨材料一致性审查。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

设计事务边界、一致性策略、多租户隔离和数据生命周期时使用。适用于高并发写入、幂等、多租户 SaaS、软删归档和审计字段设计。融合 ACID + Saga + 乐观锁 + RLS + Tenant Per Schema。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

CTO-level architectural advisor for AI-native development. Use this skill whenever you encounter code design decisions, architecture discussions, system resilience questions, or any work touching: "architecture", "design", "scale", "dependencies", "state", "failure", "blast radius", "refactor", "migrate", "optimize", "resilience", "consistency", "observability", "bottleneck", "coupling", "monolith", "microservices", "distributed", "concurrency", "data flow", "system design", or any prompt suggesting code-first thinking when design-first thinking is needed. This skill integrates with Claude Code to review generated code for architectural soundness, define design systems via design.md, and guide teams toward CTO-level thinking. Trigger aggressively on architectural questions—this is where AI adds the most leverage.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Creates a reusable Stitch Design System from theme tokens — colors, fonts, roundness. Can be applied to future screens for visual consistency.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Analyzes a Stitch project's screens and synthesizes a natural-language DESIGN.md — visual atmosphere, color palette with hex values, typography rules, and Stitch-ready prompt snippets. Use this before stitch-loop or any multi-page build to establish design consistency.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill when a customer or prospect has sent a security questionnaire, due diligence form or vendor assessment and someone asks "answer this security questionnaire", "fill in the customer's vendor assessment", "draft answers from our policies", "we have 300 questions due Friday", "reuse our previous questionnaire answers" or "which answers can we not back up". Drafts every answer from the company's own documents with a source and a confidence level, flags answers without evidence and answers that create commitments, checks consistency with past answers, and writes an answer sheet plus a list of items for owners to confirm.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use this skill when the risk register and the statement of applicability were written separately and may not agree, and the team asks "do our risks link to our controls", "traceability between risk treatment and the SoA", "why is this control applicable", "the auditor could not trace a risk to a control", "check our risk treatment plan against the SoA" or "orphan controls". Checks in both directions that every treated risk points to controls and actions, and every applicable control traces back to a risk or obligation, then writes a traceability matrix and a list of orphans and contradictions with proposed fixes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Update documentation after code changes. Scans git diff to find affected docs and updates them for consistency.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Audit and realign UI to match design system standards, spacing, tokens, and patterns. Use when the user mentions consistency, design drift, mismatched styles, tokens, or wants to bring a feature back in line with the system.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Perform a final quality pass fixing alignment, spacing, consistency, and micro-detail issues before shipping. Use when the work is functionally complete and needs finishing touches—not when the hierarchy, structure, tone, or technical foundation still need major changes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Design Shiny application UIs using bslib for theming, layout_columns for responsive grids, value boxes, cards, and custom CSS/SCSS. Covers page layouts, accessibility, and brand consistency. Use when building a new Shiny app UI from scratch, modernizing an existing app from fluidPage to bslib, applying brand theming, making a Shiny app responsive across screen sizes, or improving accessibility of a Shiny application.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Build a feature store using Feast for centralized feature management, configure offline and online stores for batch and real-time serving, define feature views with transformations, and implement point-in-time correct joins for ML pipelines. Use when managing features for multiple ML models, ensuring training-serving consistency, serving low-latency features for real-time inference, reusing feature definitions across projects, or building a feature catalog for discovery and governance.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create, validate, and convert skills for the agent ecosystem. Enforces standardized structure for consistency. Enables self-evolution by creating new skills on demand, converting MCP servers and codebases to skills.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Automated health checks for framework artifacts modified during a pipeline. Validates hook syntax, security patterns (SE-01/SE-02), skill wiring, agent consistency, and routing correctness. Invoked as the final pipeline step when framework artifacts were created, modified, or deleted.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Audit content and assets for brand compliance — style guide validation, tone of voice checking, visual identity consistency, brand asset management, and cross-channel coherence.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Final quality pass fixing alignment, spacing, consistency, interaction states, and micro-details before shipping. Executes changes (unlike design-audit and design-critique which are report-only). Triggers on polish, finishing touches, final pass, something looks off, pre-launch, good to great.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when asked to find duplication, check consistency, establish or repair SSOT, consolidate facts, or when the user says "consolidate this" or "ssotize this". Not for remote or irreversible changes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Fix Playwright automation failures against code-server (VS Code in browser). Use when: (1) trust dialog blocks all clicks — "monaco-dialog-modal-block intercepts pointer events", (2) button:has-text() finds wrong buttons behind modal dialog, (3) keyboard shortcuts don't work — Meta vs Control inconsistency, (4) VS Code extension activity bar icon not found by aria-label, (5) panels show placeholder text despite extension being "Connected". Covers trust dialog dismissal, keyboard shortcut hybrid mode, extension panel selectors, and database connection verification for Grafema extension.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. Iteratively fixes issues in source code, committing each fix atomically and re-verifying with before/after screenshots. For plan-mode design review (before implementation), use /plan-design-review. Use when asked to "audit the design", "visual QA", "check if it looks good", or "design polish".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when editing a draft, checking for AI voice patterns, reviewing prose quality, running readability analysis, auditing consistency, or validating SEO requirements on finished content.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

当用户需要验证一个信念/理论/策略/商业模式的正确性、在做决策前想检验逻辑、或在问"怎么判断这个观点对不对""这个方案有没有逻辑漏洞""怎么系统地检验一个想法"时激活。 核心信号：用户需要对某个命题做系统性的逻辑验证，而非直觉判断。 不适用于：纯情感判断、不需要逻辑验证的常识性问题、时间紧迫的直觉决策。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Write and improve prompts for Kling AI video generation, and pick the right Kling model for the job. Covers image-to-video, text-to-video, multi-shot storyboards, talking avatars from one photo plus audio, motion transfer, video editing of an existing clip, Element Reference for character consistency, Voice Control and voice cloning, native audio and dialogue, first/last frame control, credit and API costs, and troubleshooting failed generations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Local SEO audit — "best [cuisine] near me" targeting, Google Business Profile optimization, NAP consistency, citation building, restaurant schema markup

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

训练与推理数据不一致的端到端根因分析。当模块映射/值比较不足以定位问题时使用，可追踪首个可信的分歧边界，过滤融合或结构性误报，遵循生产者-消费者链，并生成包含具体假设和证据的根因报告。

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.