955건 · 관련도순
Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Evaluate Agent Skill design quality against official specifications and best practices. Use when reviewing, auditing, or improving SKILL.md files and skill packages. Provides multi-dimensional scoring and actionable improvement suggestions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Find 10x product opportunities and high-leverage improvements. Use when user wants strategic product thinking, mentions '10x', wants to find high-impact features, or says 'what would make this 10x better', 'product strategy', or 'what should we build next'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create professional Marp presentation slides with 7 beautiful themes (default, minimal, colorful, dark, gradient, tech, business). Use when users request slide creation, presentations, or Marp documents. Supports custom themes, image layouts, and "make it look good" requests with automatic quality improvements.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Execute iterative improvement workflow for QuantConnect strategies. Arguments: [strategy|issue#] [--iterations=N] [--no-backtest] [--commit]
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Optimize web images for performance with Next.js Image, responsive srcset, AVIF/WebP, lazy loading, and blur placeholders. Activate on: image optimization, LCP improvement, responsive images, AVIF, blur placeholder, next/image. NOT for: image generation/editing (use image-gen skills), SVG icon systems (use design-system-creator).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Identify and counteract cognitive biases in medical decision-making through systematic error analysis and contextual algorithm application. For diagnostic reasoning, treatment decisions, and clinical judgment improvement. NOT for basic medical knowledge, technical procedures, or non-clinical healthcare domains.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
CI/CD caching optimizer for dependency caching, Docker layer caching, and build speed improvements. Activate on: CI cache, build speed, dependency caching, Docker layer cache, turbo remote cache, GitHub Actions cache, pnpm store cache. NOT for: CI/CD pipeline creation (use github-actions-pipeline-builder), deployment strategy (use blue-green-deployment-orchestrator), Docker image building (use docker-multi-stage-optimizer).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Automatically intercepts and optimizes prompts using the prompt-learning MCP server. Learns from performance over time via embedding-indexed history. Uses APE, OPRO, DSPy patterns. Activate on "optimize prompt", "improve this prompt", "prompt engineering", or ANY complex task request. Requires prompt-learning MCP server. NOT for simple questions (just answer them), NOT for direct commands (just execute them), NOT for conversational responses (no optimization needed).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Root-causes one specific mistake the agent just made, such as not committing despite instructions to, by checking it against the loaded AGENTS.md, CLAUDE.md, skills, and Beads memories, delegating the investigation to a separate agent where the harness supports one; proposes concrete context improvements, and lets the user choose which to apply and how to remediate. Use when the user invokes `/learn` or `$learn`, with or without a description of the mistake, including `/learn /qs`-style shorthand naming the corrective command. For a broad end-of-session documentation sweep, use `documentation-updates` (`/reflect`) instead.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Identifies essential genes from CRISPR-Cas9 fitness screens using BAGEL2 (Kim & Hart 2021 Genome Med), a Bayesian classifier scoring per-gene Bayes Factors via log-likelihood ratios over per-sgRNA fold changes, calibrated against CEGv2 core-essentials (Hart 2017 G3, ~684 genes) and NEGv1 non-essentials (Hart 2014, ~927 genes). Covers the fc + bf + pr workflow, the linear-extrapolation improvement over BAGEL1 truncation, multi-target off-target correction, tumor-suppressor sensitivity (BAGEL2 detects enrichment), and BF calibration (BF >6 ≈ 90% posterior per Hart 2017; ~5% FDR by BAGEL convention). Use when classifying essential vs non-essential genes, calibrating BAGEL2 thresholds against PR curves, identifying tumor suppressors alongside essentials, comparing BAGEL2 hits to MAGeCK / drugZ, or generating publication-quality essentiality calls.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Analyzes harness trace logs to surface recurring failure patterns and suggest harness improvements. Scatter-gather across last N runs with a mandatory HITL gate before any change is applied.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when analyzing harness trace logs to surface recurring failure patterns and suggest harness improvements. Scatter-gather pattern across last N runs with mandatory HITL gate before any change is applied. Triggers on /mk:trace-analyze, "analyze traces", "find patterns in harness runs", or after a model upgrade flagged dead-weight-audit-needed.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use for deep Vue 3 best-practices review, recommendations, and the full ordered authoring workflow — built-in components (Teleport, Suspense, KeepAlive, Transition, TransitionGroup), animation techniques, slots, fallthrough attrs, custom directives, async components, render functions, plugins, and the post-functionality performance pass. Complements mk:vue (the everyday Composition API quick-reference). Invoke for "review my Vue", "Vue best practices", "recommend improvements", or non-trivial feature work needing the ordered workflow.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when writing, reviewing, or optimizing React/Next.js code. Triggers on .tsx/.jsx files, React component work, Next.js routes, bundle optimization, re-render issues, or performance improvements. Auto-activates alongside mk:typescript when React project detected.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Opt-in post-PR analysis and improvement suggestions for code quality enhancement
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Read-only report of improvement suggestions from eval-core analysis engine
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Apply verified improvement suggestions from eval-core analysis to omcustom configuration
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when user says "simmer this", "refine this", "hone this", "iterate on this", or asks to improve a specific artifact over multiple rounds. Runs an iterative refinement loop with investigation-first judges that read the code, understand the problem, and propose evidence-based improvements. Auto-selects single judge or multi-judge board based on complexity. Works on any artifact type: documents, prompts, specs, emails, creative writing, API designs, pipelines, codebases. Supports multi-file workspace targets, runnable evaluators, and open-ended optimization (model selection, pipeline topology, prompt tuning).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Turn friction you just hit into a concrete change to the workflow, so the same problem doesn't recur.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill recommends educating patients and families about the clinical features of remission in Cushing's syndrome when a patient achieves biochemical remission after treatment. Use when a CS patient has postoperative normal cortisol levels, reports symptom improvement, and requires guidance on long-term expectations and monitoring for recurrence.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Optimizes application performance. Use when performance requirements exist, when you suspect performance regressions, or when Core Web Vitals or load times need improvement. Use when profiling reveals bottlenecks that need fixing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.