「20」の検索結果

연봉 갱신 시 사용하는 연봉계약서 자동 작성 스킬. 기본급·수당·연봉 총액 명시, 2026년 최저임금 10,320원 검증, 고정OT 포함 포괄임금제, 5인 미만/이상 분기 지원.

日本語の概要は準備中です。原文の説明を表示しています。

한국 사업자를 위한 근로계약서 자동 작성 스킬. 주40시간 정규직·계약직, 근로기준법 §17 필수 기재 항목, 2026년 최저임금(10,320원/시), 4대보험 의무를 반영. 5인 이상/미만, 수습기간, 고정OT, 포괄임금제 지원.

日本語の概要は準備中です。原文の説明を表示しています。

유연근무제(탄력근로·선택근로·재택근무) 적용 근로계약서 자동 작성 스킬. 근로기준법 §51·§52 서면합의 요건, 5인 이상/미만 분기, 2026년 최저임금(10,320원/시) 자동 검증.

日本語の概要は準備中です。原文の説明を表示しています。

단시간 근로자·아르바이트용 근로계약서 자동 작성 스킬. 카페·편의점·일반 업종 지원, 주15시간 이상/미만 분기, 2026년 최저임금(10,320원/시) 자동 검증, 5인 이상/미만 분기, 주휴수당 자동 계산.

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기존 근로계약서의 근로조건을 변경할 때 사용하는 근로조건 변경 합의서 자동 작성 스킬. 임금·근무장소·업무내용·근무시간 변경, 5인 미만/이상 분기, 2026년 최저임금 10,320원 검증 포함.

日本語の概要は準備中です。原文の説明を表示しています。

Turn a YouTube video idea into a designer-ready thumbnail brief: focal subject, face and emotion, a text overlay of 4 words or fewer that the title does not repeat, contrast and composition, and 2 to 3 A/B concepts for Test and Compare. Built on 2026 principles (one focal point, legible at 120 pixels, complements the title). Outputs the brief plus the Publora attach step (the image upload itself is out of band). Use to plan a thumbnail. Not for title words (use yt-title-optimizer).

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跨版本符号迁移与二进制差分。当你有旧版本的符号/逆向结果，需要快速迁移到新版本时使用。 适用场景：内核缺 PDB 用旧版符号推导、程序更新后批量迁移函数名、游戏反作弊更新后快速定位新偏移。 核心方法：用 LLM 做结构化差异比对，程序化输入输出，成本极低（200 函数 ~1 元）。 触发关键词：符号迁移、bindiff、跨版本、PDB 缺失、函数偏移迁移、symbol migration、binary diff、版本对比。

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主动渗透测试工具链。覆盖信息收集、端口扫描、漏洞扫描、Web 渗透、SQL 注入、目录爆破、密码破解等场景。 通过 MCP server（pentestMCP / mcp-security-hub）将 20+ 安全工具暴露给 AI agent。 触发关键词：渗透测试、端口扫描、Nmap、漏洞扫描、Nuclei、SQL 注入、SQLMap、目录爆破、FFUF、密码破解、Hashcat、信息收集、子域名、Web 渗透、ZAP、Burp。

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建立设计令牌系统时使用。适用于设计系统建立、跨平台一致性、设计代码同步。优先使用 W3C DTCG 2025.10 标准 + 三层 Token + JSON 输出。

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Scout the TouchDesigner community for what's HYPED right now — community showcases, recent tutorials, generative-AI bridges, hardware interaction trends, visual-aesthetic trends of 2025-2026 — then propose tdmcp tools that ride those trends AND are easy to build. Use whenever the user wants to brainstorm new feature ideas based on what's trending in TouchDesigner, asks for 'hype' or 'trending' features, asks 'what are people doing in TD right now / what's hot / what's hype', wants tools inspired by community trends, asks to scout TD trends/aesthetics/integrations, or says things like 'ideias hype', 'novas ideias', 'o que está em alta', 'criar ferramentas para o que está bombando', 'tendências do TouchDesigner'. Also for follow-ups: refresh, rescout one surface, re-rank under another profile, deepen a trend, or filter for buildable-easy items. This is an EXTERNAL trend ideation harness — complementary to tdmcp-feature-discovery (which is INTERNAL gap analysis). It produces `_workspace/hype-scout/HYPE_TOOL_BACKLOG.md` ranked by Hype × Build-Ease; it does NOT build. Once a feature is chosen from the backlog, hand it to tdmcp-pipeline.

日本語の概要は準備中です。原文の説明を表示しています。

Scout ONE external surface of the TouchDesigner community for what's HYPED in 2025-2026 that could become a tdmcp tool. Use when a td-trend-scout sub-agent is assigned a surface (community-showcase, tutorials, generative-ai, hardware-interactive, or vfx-aesthetics) during the tdmcp-hype-scout harness — produces `_workspace/hype-scout/01_scout_<surface>.md` with cited trend candidates ranked by hype intensity, recency, and build-ease in tdmcp.

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Multi-backend database security auditor. Audits Supabase, Firebase (Firestore/RTDB/Storage/Functions/Remote Config), MongoDB (self-hosted + Atlas), self-hosted PostgreSQL, and self-hosted MySQL for RLS/rules misconfigurations, exposed credentials, auth bypasses, MongoBleed (CVE-2025-14847), pgBouncer CVE-2025-12819, mysql_native_password drift, ghost auth, and storage exposures. Use this skill whenever the user mentions database security, RLS or rule audits, security review, penetration testing a vibe-coded app, checking if their DB is exposed, hardening a backend, fixing security rules, or auditing apps built with Lovable/Bolt/Replit/Cursor/Claude Code on any of these backends. Trigger on phrases like 'is my app secure', 'check my database', 'audit my Firebase', 'audit my MongoDB', 'audit my Postgres', 'audit my Supabase', 'is my DB exposed', or any cross-backend variant ('audit my full stack').

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Use when benchmarking, profiling, or A/B-testing CUDA kernels or end-to-end perf in the imp inference engine on RTX 5090 (sm_120), including refreshing tests/perf_baseline.json or publishing numbers to docs/BENCHMARKS.md and the README. Triggers on "benchmark kernel", "profile cuda", "ncu", "nsys", "kernel timing", "kernel sum", "occupancy", "bandwidth bound", "compute bound", "roofline", "perf baseline", "is this regression real", "decode dropped", "aggregate throughput", "two-image A/B", "prefill kernel A/B". Do NOT use for writing/optimizing kernel code (sm120-cuda-expert) or output-quality checks (check-degeneration).

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Source pre-2016 cinema with gothic/occult sensibility, literary texture, and historical grandeur — build watchlists, curate Criterion/MUBI picks. Uses Perplexity for film discourse, Exa for web search, Firecrawl for scraping. Triggers on film recommendations, watchlist, gothic cinema, occult film, arthouse, pre-2016 movies.

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Generate 20,000+ particle swarm simulators in two modes: sandbox (complete Three.js host runtime with gesture controls, security validation, code injection pipeline) and sim (behavior function bodies that position/color particles via a sandboxed API). The AI writes ONLY a function body — the host handles rendering, input, and security. Triggers on particle swarm, swarm simulator, particle behavior, swarm sandbox, gesture particles, 20K particles, particle function body, swarm sim, particle playground.

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行为面试 skill。帮求职者挖掘真实经历、用 STAR/CAR 结构化、映射能力标签、构建可复用的中英双语故事库（Story Bank）；并能接入 JD + 简历，针对具体岗位生成 Top 20 BQ 选题 + 基于真实经历的 STAR 准备模板（HTML 报告）。不是背答案，而是建立可复用的职业叙事体系，让任何行为面试题都能自然作答。关键词：behavioral question, BQ, 行为面试, STAR, 故事库, Amazon LP, 职业故事, tell me about a time, 面试准备, JD 面试题预测, top 20 题。

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Etsy SEO optimization for existing and new listings. Auto-detects REWRITE (when user pastes a current title + tags + description) or CREATE (when user gives a short product context). Triggers on "rewrite this listing", "optimize my Etsy listing", "fix my title and tags", "create new listing", "make a new Etsy listing". Uses live Etsy autocomplete + competitor SERP scraping for evidence-driven keyword research. Enforces 2026 Etsy rules — tag ≤20 chars, primary keyword in first 40 chars, indexing spread across title/tags/attributes/description/hero alt, NLP-aware writing, trademark stoplist scan. When the user's problem isn't SEO (CTR, conversion, photos, price, saturated niche), it says so directly and routes to concrete next steps. Silently maintains a markdown listing database at ~/etsy-listings/ for cross-session memory on Claude/Cowork. Catches duplicate primary keywords across the user's own listings.

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当用户直接要求进行数据集压缩测评，或在量化调优过程中需要使用 AISBench 评测工具输出数据集精度等场景时使用。 本 Skill 负责：使用 AISBench 数据集压缩代码、用 RBF Kernel Herding 算法生成压缩后的数据子集（coreset），并按用户目标交付两种产物之一： ① 接入量化调优主流程：产出独立的 coreset 数据集配置（不覆盖原始数据），回传「全集 config_name + coreset config_name」给编排层，供 evaluation.yaml 切换； ② 仅数据集压缩测评（不做量化调优）：基于 example 模板生成「全集测试脚本」和「子集测试脚本」两份 shell 脚本。 暂时支持 AIME 2025 和 GPQA，其他数据集需要再结合 aisbench tools目录下 herding_coreset_selector 源码进行分析。

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Create a new experiment folder by copying reference/ as a template. Auto-generates SESSION_NOTES.md and run.sh. Claude experiments use expA00, A01, ...; human experiments use exp200, 201, ... in sequential numbering.

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中文去 AI 腔一整套（装完即用，零 API Key —— 装了本 skill 的 agent 自己就是那个 LLM）。 六个流程：① 生成即去 AI —— 写中文时按本 skill 的写作指南落笔，初稿就不带 AI 腔； ② 复查改写 —— 产出后对照本 skill 的清单再过一遍，定点拆模板句式； ③ Python 词语替换 —— ./humanize replace 按文体自动路由词表（学术 120+ 条 / 通用 220+ 条），只做短语级、只在子句边界替换，改完自动核对数字/专名/段落； ④ Claude 腔转中文 —— 把 Claude 助手腔的中文改写成平实中文， 规则提炼自 gvzdv/claudish-to-english 并本地化； ⑤ 去水印 —— ./humanize watermark 扫清零宽字符/双向控制符/同形替身， 并对照 guillaumemeyer/watermarks-remover 说明统计水印的边界； ⑥ 纠错顺句 —— 修错词、病句、标点，拗口和用词不准处轻手顺一顺；改动范围有硬校验。 另有检测（0-100 分）、风格转换、学术降重等 CLI。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "make text human-like", "去ai化", "改成人话", "去机器味", "长文本改写", "小说改写", "写一篇", "claudish", "去claude腔", "助手腔", "去水印", "watermark remover", "remove watermark"

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Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape. Activate on "find expungement data", "scrape state laws", "legal research", "court URLs", "statute sources", "Clean Slate laws", "automatic expungement research". NOT for interpreting laws (use national-expungement-expert), building UI, or legal advice.

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Run MATLAB R2026a tasks from Codex with reliable MCP-based execution, logs, artifacts, toolbox inventory, smoke tests, and reproducible validation. Use whenever MATLAB code, .m/.mlx scripts, MATLAB tests, local toolbox probing, or command-line automation is needed.

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MATLAB R2026a code generation and deployment workflow for MATLAB Coder, Simulink Coder, Embedded Coder, GPU Coder, HDL Coder, fixed-point conversion, MEX validation, and embedded deployment readiness. Use whenever the user asks to generate C/C++/CUDA/HDL/code, deploy algorithms, or validate generated code.

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MATLAB R2026a robotics and autonomy workflow for ROS Toolbox, Robotics System Toolbox, Navigation Toolbox, UAV Toolbox, sensor fusion, trajectory planning, simulation, and reproducible robot experiments. Use for ROS/ROS 2 bags, robot models, path planning, SLAM, state estimation, and autonomy prototyping.

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