2.7천건 · 관련도순
Analyze binaries or protocols you own (or have license to inspect) to improve security, compatibility, or incident response. Not for cracking, DRM bypass, or malware creation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Improve detections, hardening, and response for the estate you defend. Detection-as-code and control design, not offense.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Audit web pages for performance optimization following PageSpeed Insights guidelines. Use when analyzing page performance, optimizing web applications, reviewing performance metrics, implementing Core Web Vitals improvements, or when the user mentions page speed, performance optimization, Lighthouse scores, or Core Web Vitals.
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-to-FDR calibration (BF >6 ≈ FDR 0.05 from Hart 2017). 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.
Refactor Spring Boot and Java code to improve maintainability, readability, and adherence to enterprise best practices. This skill transforms messy Spring Boot applications into clean, well-structured solutions following SOLID principles and Spring Boot 3.x conventions. It addresses fat controllers, improper transaction boundaries, field injection anti-patterns, and scattered configuration. Leverages Java 21+ features including record patterns, pattern matching for switch, virtual threads, and sequenced collections.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Improve unclear UX copy, error messages, microcopy, labels, and instructions to make interfaces easier to understand. Use when the user mentions confusing text, unclear labels, bad error messages, hard-to-follow instructions, or wanting better UX writing.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Improve interface resilience through better error handling, i18n support, text overflow handling, and edge case management. Makes interfaces robust and production-ready. Use when the user asks to harden, make production-ready, handle edge cases, add error states, or fix overflow and i18n issues.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Designs and improves onboarding flows, empty states, and first-run experiences to help users reach value quickly. Use when the user mentions onboarding, first-time users, empty states, activation, getting started, or new user flows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Improves typography by fixing font choices, hierarchy, sizing, weight, and readability so text feels intentional. Use when the user mentions fonts, type, readability, text hierarchy, sizing looks off, or wants more polished, intentional typography.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Improve layout, spacing, and visual rhythm. Fixes monotonous grids, inconsistent spacing, and weak visual hierarchy. Use when the user mentions layout feeling off, spacing issues, visual hierarchy, crowded UI, alignment problems, or wanting better composition.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Review a feature and enhance it with purposeful animations, micro-interactions, and motion effects that improve usability and delight. Use when the user mentions adding animation, transitions, micro-interactions, motion design, hover effects, or making the UI feel more alive.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Improve test value and feedback cost when auditing slow, flaky, redundant or brittle tests; choosing tests during implementation; or reviewing test changes before a commit or PR. Keep ordinary implementation and pre-commit use scoped to the affected behavior, not a repository-wide audit.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design, audit, and improve analytics tracking systems that produce reliable, decision-ready data.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Forensic root cause analyzer for Antigravity sessions. Classifies scope deltas, rework patterns, root causes, hotspots, and auto-improves prompts/health.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
蓄積された observations を分析し、SKILL.md への改善提案を生成する。 Observe → Inspect → Amend → Evaluate ループの Inspect/Amend フェーズ。 `--apply` フラグで承認後の適用も可能。
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Targeted deep research to fill a specific gap in an existing thesis. Use when user says "deepen", "flesh out", "expand on", "fill in", or specifies a thesis section to improve. Also supports --sync-metrics mode — detects stale financial metrics across every in-scope analytical section of a thesis (not just Key Metrics or Summary) and coherently updates every sentence that depends on them, using a Key-Metrics-table / FMP / web-search waterfall. Use when user says "sync metrics", "update the numbers throughout the note", or "fix stale figures across the whole thesis". The batch form `--sync-metrics --all-flagged` syncs every thesis flagged by the latest `$numbers --all-open` in one operation — detection fanned out to capped READ-ONLY agents, one consolidated confirmation gate, direct sequential writes (agents never write).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Targeted deep research to fill a specific gap in an existing thesis. Use when user says "deepen", "flesh out", "expand on", "fill in", or specifies a thesis section to improve. Also supports --sync-metrics mode — detects stale financial metrics across every in-scope analytical section of a thesis (not just Key Metrics or Summary) and coherently updates every sentence that depends on them, using a Key-Metrics-table / FMP / web-search waterfall. Use when user says "sync metrics", "update the numbers throughout the note", or "fix stale figures across the whole thesis". The batch form `--sync-metrics --all-flagged` syncs every thesis flagged by the latest `/numbers --all-open` in one operation — detection fanned out to capped READ-ONLY agents, one consolidated confirmation gate, direct sequential writes (agents never write).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill when the user requests to generate, create, or improve documentation for code, APIs, libraries, repositories, or software projects. Supports README generation, API reference documentation, inline code comments, architecture documentation, changelog generation, and developer guides. Trigger on requests like "document this code", "create a README", "generate API docs", "write developer guide", or when analyzing codebases for documentation purposes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.