Trending Skills
The hottest skills gaining momentum in the community right now.
google-cloud-recipe-onboarding
by google
Guidance for a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource.
Lessons Log
by product-on-purpose
A curated collection of 24 best-practice, plug-and-play product management “agent skills” plus templates and workflow bundles for consistent, professional PM outputs.
cloud-run-basics
by google
Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).
google-cloud-recipe-auth
by google
Provides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.
🎨 UI 设计规范
by Project-N-E-K-O
Project N.E.K.O. 胶囊化 UI、品牌蓝视觉系统规范
weekly-review
by cursor
Produce a weekly synthesis of authored commits with highlights by bugfix, tech debt, and net-new work
create-changelog-announcement
by Agenta-AI
Use this skill to create and publish changelog announcements for new features, improvements, or bug fixes. This skill handles the complete workflow - creating detailed changelog documentation pages, adding sidebar announcement cards, and ensuring everything follows project standards. Use when the user mentions adding changelog entries, documenting new features, creating release notes, or announcing product updates.
product-photography
by inference-sh
"AI product photography with studio lighting, lifestyle shots, and packshot conventions. Covers angles, backgrounds, shadow types, hero shots, and e-commerce image requirements. Use for: product photos, e-commerce images, Amazon listings, packshots, lifestyle photography. Triggers: product photography, product photo, packshot, e-commerce photography, product shot, product image, studio photography, lifestyle product, amazon product photo, product listing image, hero shot, product mockup, commercial photography"
product-photography
by inference-sh
"AI product photography with studio lighting, lifestyle shots, and packshot conventions. Covers angles, backgrounds, shadow types, hero shots, and e-commerce image requirements. Use for: product photos, e-commerce images, Amazon listings, packshots, lifestyle photography. Triggers: product photography, product photo, packshot, e-commerce photography, product shot, product image, studio photography, lifestyle product, amazon product photo, product listing image, hero shot, product mockup, commercial photography"
agent-browser
by inference-sh
"Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video"
data-visualization
by inference-sh
"Data visualization with chart selection, color theory, and annotation best practices. Covers chart types (bar, line, scatter, heatmap), axes rules, and storytelling with data. Use for: charts, graphs, dashboards, reports, presentations, infographics, data stories. Triggers: data visualization, chart, graph, data chart, bar chart, line chart, scatter plot, data viz, visualization, dashboard chart, infographic data, data presentation, chart design, plot, heatmap, pie chart alternative"
flux-image
by inference-sh
"Generate images with FLUX models (Black Forest Labs) via inference.sh CLI. Models: FLUX Dev LoRA, FLUX.2 Klein LoRA with custom style adaptation. Capabilities: text-to-image, image-to-image, LoRA fine-tuning, custom styles. Triggers: flux, flux.2, flux dev, flux schnell, flux pro, black forest labs, flux image, flux ai, flux model, flux lora"
grillme
by brycewang-stanford
苏格拉底诘问式研究选题Skill。通过连续追问帮你厘清研究思路、聚焦研究子领域、明确研究问题(RQ)，识别出未被研究过的新意选题。触发词：帮我选题/研究问题不清晰/想做一个有新意的论文/不断问我问题/厘清思路
google-cloud-recipe-networking-observability
by google
Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs, NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics.
polish
by pbakaus
Final quality pass before shipping. Fixes alignment, spacing, consistency, and detail issues that separate good from great.
optimize
by pbakaus
Improve interface performance across loading speed, rendering, animations, images, and bundle size. Makes experiences faster and smoother.
Scientific Writing
by brycewang-stanford
🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文，并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.
Full-empirical-analysis-skill-Stata
by brycewang-stanford
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc + binscatter. Defaults to economics empirical-paper style (AER / QJE / AEJ) — every run produces a publication-ready output set with a multi-column regression table (M1→M6 progressive controls/FE) as the centerpiece, plus Table 1 (descriptives), mechanism / heterogeneity / robustness tables, and event-study + coefficient + trend figures. Covers the full 8-step Stata pipeline an applied economist runs on every paper — (1) data import & cleaning (use/import, destring, misstable, duplicates, merge assert), (2) variable construction (gen/egen/winsor2/xtile/xtset with L./F./D.), (3) descriptive statistics & Table 1 (tabstat/balancetable/asdoc), (4) classical diagnostic tests (sktest/swilk/hettest/imtest/xtserial/xttest3/vif/dfuller/kpss/hausman/estat overid), (5) baseline modeling (reg/xtreg/reghdfe/ivreg2/ivregress/csdid/did_imputation/eventstudyinteract/sdid/rdrobust/synth/psmatch2/teffects/heckman/qreg/ppmlhdfe), (6) robustness battery (bacondecomp/honestdid/rwolf/ritest/wildbootstrap/oster), (7) further analysis (subgroup/triple-diff/interactions/medsem/marginsplot/binscatter by group), (8) publication-ready tables & figures (esttab/outreg2/estout/coefplot/marginsplot/rdplot/twoway combined). Also covers two parallel domain modes that share the same 8-step scaffolding — Mode A — Epidemiology / public health (target-trial emulation, IPTW + g-formula + TMLE doubly-robust triplet via teffects ipw / teffects ipwra / teffects aipw / eltmle, Mendelian randomization via mrrobust (IVW / Egger / weighted median) and mregger / mrpresso, KM / Cox / AFT / RMST survival via sts / stcox / streg / strmst2, E-value sensitivity via evalue (Linden-Mathur), principal stratification — STROBE / TRIPOD reporting), and Mode B — ML causal inference (DML via ddml / pdslasso, S/T/X/R/DR meta-learners via crforest and ddml interactive, causal forest via crforest / cforest, BART/BCF via bart / bartCause-style externals, CATE distribution + policy tree via crforest, off-policy evaluation, conformal causal externals, fairness audit, DAG learning via pcalg / external Python callouts). Use when the user asks for a complete Stata empirical analysis, wants a reproducible .do-file pipeline, needs a Stata counterpart to the Python StatsPAI / Full-empirical-analysis-skill, or names a specific Stata step in isolation ("run reghdfe with two-way clustering", "csdid event study", "winsor2 at 1%", "esttab to LaTeX", "coefplot with CI", "ivreg2 weak-IV test", "synth_runner placebos", "teffects psmatch balance check"). Mode A triggers on "target trial emulation Stata", "teffects ipw aipw", "eltmle", "mrrobust", "mregger weighted median", "stcox AFT survival", "strmst2", "evalue Stata", "STROBE Stata", "公共健康 Stata", "流行病学 Stata". Mode B triggers on "ddml Stata", "pdslasso", "crforest causal forest Stata", "policy tree Stata", "因果机器学习 Stata".
clay-policy-guardrails
by Dicklesworthstone
Implement Clay lint rules, policy enforcement, and automated guardrails. Use when setting up code quality rules for Clay integrations, implementing pre-commit hooks, or configuring CI policy checks for Clay best practices. Trigger with phrases like "clay policy", "clay lint", "clay guardrails", "clay best practices check", "clay eslint".
apollo-cost-tuning
by Dicklesworthstone
Optimize Apollo.io costs and credit usage. Use when managing Apollo credits, reducing API costs, or optimizing subscription usage. Trigger with phrases like "apollo cost", "apollo credits", "apollo billing", "reduce apollo costs", "apollo usage".
Vanilla JS UI Race Conditions (VRM vs Live2D)
by Project-N-E-K-O
Dealing with delayed DOM generation, lazy loading, and optimistic state synchronization in vanilla JavaScript without a reactive framework.
marp-slides-creator
by brycewang-stanford
专业Marp演示文稿制作助手。支持完整工作流程：工作空间初始化、内容分析、slides制作、多维度审阅、中文语言规范审阅（中文演示文稿）、PNG转换检查、终稿确定。所有产出物集中管理在项目工作文件夹中。当用户提到"制作slides"、"做PPT"、"演示文稿"、"Marp"、"幻灯片"、"presentation"等关键词时自动启用。Professional Marp presentation assistant with complete workflow: workspace initialization, content analysis, slide creation, multi-dimensional review, Chinese language review (for Chinese presentations), PNG conversion check, and finalization. All outputs organized in project workspace.
Scientific Hypothesis Generation
by brycewang-stanford
🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文，并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.
gke-basics
by google
"Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inference, GKE upgrade, GKE observability, GKE multi-tenancy, GKE batch, GKE HPC, GKE compute class."