Skill-uri pentru agenți pe care le poți verifica înainte să le instalezi
Skill-uri SKILL.md publice din depozite GitHub cu peste 50 de stele și de la producători, scanate și evaluate. Instalează oricare dintre ele cu o singură comandă în Claude Code, Cursor, Codex, GitHub Copilot sau Gemini CLI.
18.069 de skill-uri din 635 de depozite · actualizat acum 2 minute
3.489 de skill-uri
- monitor-experimentbrycewang-stanford/Auto-Empirical-Research-SkillsMonitor running experiments, check progress, collect results. Use when user says "check results", "is it done", "monitor", or wants experiment output.AlteleFără avertismente★ 4,7 K↓ —
- amazon-profit-analyzernexscope-ai/Amazon-SkillsComprehensive Amazon profit analysis and revenue optimization. Revenue waterfall analysis, hidden fee identification, ACoS impact assessment, return cost calculation, and profitability optimization strategies. Use when the user asks about Amazon profit analysis, profitability calculation, fee analysis, margin optimization, or revenue breakdown.AlteleFără avertismente★ 793↓ —
- fletcherbrycewang-stanford/Auto-Empirical-Research-SkillsDefamiliarization audit for empirical output. Systematically interrogates every feature of a figure, table, or set of results — not just the main finding. Named for Jason Fletcher, who asked about the spike at t=1 when everyone else was looking at t=2. Use when you have output and are about to interpret or report it.AlteleFără avertismente★ 4,7 K↓ —
- referee-responsebrycewang-stanford/Auto-Empirical-Research-SkillsStructure responses to referee reports for R&R submissionsAlteleFără avertismente★ 4,7 K↓ —
- ols-regressionbrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a regression model", "check regression diagnostics", "OLS假设", "最小二乘法", "线性回归", "回归系数", "残差检验", "异方差", "多重共线性", "普通最小二乘", "稳健标准误", "回归诊断"AlteleFără avertismente★ 4,7 K↓ —
- r-oopbrycewang-stanford/Auto-Empirical-Research-SkillsR object-oriented programming guide for S7, S3, S4, and vctrs. Use when designing R classes or choosing an OOP system.AlteleFără avertismente★ 4,7 K↓ —
- analyze-resultsbrycewang-stanford/Auto-Empirical-Research-SkillsAnalyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.AlteleFără avertismente★ 4,7 K↓ —
- did-analysisbrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics skill for Difference-in-Differences (DID) analysis. Activates when the user asks about: "difference in differences", "DID", "DiD", "diff-in-diff", "parallel trends", "treatment group", "control group", "pre-treatment", "post-treatment", "policy evaluation", "natural experiment", "staggered DID", "event study regression", "two-way fixed effects DID", "callaway santanna", "sun and abraham", "双重差分", "倍差法", "平行趋势", "处理组", "对照组", "政策评估", "事件研究", "交错DID", "渐进处理"AlteleFără avertismente★ 4,7 K↓ —
- training-checkbrycewang-stanford/Auto-Empirical-Research-SkillsPeriodically check WandB metrics during training to catch problems early (NaN, loss divergence, idle GPUs). Avoids wasting GPU hours on broken runs. Use when training is running and you want automated health checks.AlteleFără avertismente★ 4,7 K↓ —
- stata-resultsbrycewang-stanford/Auto-Empirical-Research-SkillsFetch and display stored r(), e(), and s() results from the last Stata command.AlteleFără avertismente★ 4,7 K↓ —
- CTF•杂项asdfgh1445/ctf-super-hub用于编码题、pyjail、bash jail、RF/SDR、DNS 异常、Unicode、奇特语言、QR、音频、约束求解、博弈论与沙箱逃逸等跨类或边缘 CTF 题;触发名:ctf-miscAlteleFără avertismente★ 837↓ —
- feishu-notifybrycewang-stanford/Auto-Empirical-Research-SkillsSend notifications to Feishu/Lark. Internal utility used by other skills, or manually via /feishu-notify. Supports push-only (webhook) and interactive (bidirectional) modes. Use when user says "发飞书", "notify feishu", or other skills need to send status updates.AlteleFără avertismente★ 4,7 K↓ —
- web-accessbrycewang-stanford/Auto-Empirical-Research-Skills所有联网操作必须通过此 skill 处理，包括：搜索、网页抓取、登录后操作、网络交互等。触发场景：用户要求搜索信息、查看网页内容、访问需要登录的网站、操作网页界面、抓取社交媒体内容（小红书、微博、推特等）、读取动态渲染页面、以及任何需要真实浏览器环境的网络任务。AlteleFără avertismente★ 4,7 K↓ —
- ml-causalbrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics skill for machine learning methods in causal inference. Activates when the user asks about: "causal forest", "generalized random forest", "GRF", "double machine learning", "DML", "debiased machine learning", "LASSO for variable selection", "post-LASSO", "heterogeneous treatment effects", "CATE", "conditional average treatment effect", "BLP analysis", "CLAN analysis", "causal tree", "honest estimation", "因果森林", "双重机器学习", "异质性处理效应", "条件平均处理效应", "LASSO变量选择", "机器学习因果推断", "去偏机器学习"AlteleFără avertismente★ 4,7 K↓ —
- stata-lintbrycewang-stanford/Auto-Empirical-Research-SkillsRun static analysis on a Stata .do or .ado file and report style and best-practice issues.AlteleFără avertismente★ 4,7 K↓ —
- stata-helpbrycewang-stanford/Auto-Empirical-Research-SkillsLook up Stata command documentation and display formatted help text.AlteleFără avertismente★ 4,7 K↓ —
- data-docbrycewang-stanford/Auto-Empirical-Research-SkillsDocument datasets, variables, sources, and merge keys for replicationAlteleFără avertismente★ 4,7 K↓ —
- figurebrycewang-stanford/Auto-Empirical-Research-SkillsEconometrics skill for generating publication-quality figures for top economics journals. Activates when the user asks about: "econometric figure", "publication figure", "journal figure", "AER figure", "QJE figure", "event study plot", "coefficient plot", "coefplot", "binned scatter", "binscatter", "RDD plot", "parallel trends plot", "kernel density", "distribution plot", "time series plot", "map", "figure formatting", "academic plot", "论文图表", "学术图", "系数图", "事件研究图", "散点图", "分布图", "趋势图", "回归可视化"AlteleFără avertismente★ 4,7 K↓ —
- vast-gpubrycewang-stanford/Auto-Empirical-Research-SkillsRent, manage, and destroy GPU instances on vast.ai. Use when user says "rent gpu", "vast.ai", "rent a server", "cloud gpu", or needs on-demand GPU without owning hardware.AlteleFără avertismente★ 4,7 K↓ —
- doctorbrycewang-stanford/Auto-Empirical-Research-SkillsSystem diagnostics and health checks for Diverga plugin. OpenClaw-style Check-Report-Fix pattern with 5-layer diagnostics. Triggers: /diverga:doctor, diverga doctor, system check, diagnose, 진단AlteleFără avertismente★ 4,7 K↓ —
- helpbrycewang-stanford/Auto-Empirical-Research-SkillsDiverga help guide - displays all 24 agents across 9 categories, commands, and usage examples. Triggers: help, guide, how to use, 도움말AlteleFără avertismente★ 4,7 K↓ —
- statabrycewang-stanford/Auto-Empirical-Research-SkillsShow mcp-stata identity, connected tools, and status. Use when the user asks if mcp-stata is available, asks about access to the toolkit, or asks what Stata tools are connected.AlteleFără avertismente★ 4,7 K↓ —
- i2brycewang-stanford/Auto-Empirical-Research-SkillsScreening Assistant - AI-PRISMA 6-dimension screening with Groq LLM (100x cheaper) Supports two project types with different confidence thresholds Use when: screening papers, PRISMA screening, inclusion/exclusion criteria Triggers: screen papers, PRISMA screening, inclusion criteria, exclusion criteria, AI screeningAlteleFără avertismente★ 4,7 K↓ —
- scvi-toolsaipoch/open-scienceProbabilistic single-cell RNA-seq with scvi-tools — scVI for a batch-corrected latent space, scANVI for semi-supervised label transfer, and Bayesian differential expression. Reach for this skill to integrate scRNA-seq batches, embed cells for clustering, transfer annotations from a reference onto a query, or score differentially expressed genes per cluster. For spatial deconvolution / mapping use the cell2location, DestVI, or Tangram methods instead.AlteleFără avertismente★ 5,4 K↓ —
qiuzhi2046-skill
momozi1996/awesome-ai-persona-skills
AlteleActualizat 2 sept. 2026
De la autor
秋芝2046（前产品经理，AI Native创作者）的AI科普内容创作思维——爆肝实操导向、痛点前置产品思维、全平台内容矩阵、B站深度+抖音短平快+飞书系统化。 触发词：「秋芝2046视角」「像秋芝2046那样写」「AI科普教程」「DeepSeek教程」「One-Click解决一切」。 擅长：AI工具测评与推荐、AI教程设计（幼儿园→专业级）、技术热点快速响应、AIGC内容实验、多平台内容矩阵运营、飞书知识库架构、AI春晚级别的项目管理。
Instalare
npx skills add momozi1996/awesome-ai-persona-skills --skill qiuzhi2046-skill -a claude-code
Se instalează în .claude/skills/qiuzhi2046-skill/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Descarcă .zip
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
La ce are acces
Doar instrucțiuniNu am văzut acces la rețeaLicență: MIT
Verificări de siguranță pe SKILL.md
Niciun avertisment.
De ce 85
Securitate100
Proveniență76
Întreținere85
Licență100
Adopție49
Fișiere (7)
- SKILL.md
- references/research/01-writings.md
- references/research/02-conversations.md
- references/research/03-expression-dna.md
- references/research/04-external-views.md
- references/research/05-decisions.md
- references/research/06-timeline.md