Skills
开放的 AI 智能体 Skills 注册表,收录结构化提示词和工作流,并提供推荐模型、示例提示词与兼容工具。
Skills
153
类别
9
兼容工具
5
贡献者
2
Adds clear, accurate inline comments and API doc blocks to existing code without changing behavior. Generates docstrings and structured comments (JSDoc, Google/NumPy style, Javadoc, Rustdoc) that explain intent, parameters, return values, side effects, and edge cases, while avoiding noisy comments that merely restate the code.
Optimizes web content for search engines and readers. Performs keyword analysis and intent mapping, improves titles, meta descriptions, headings, and internal linking, and generates structured data (JSON-LD) while keeping copy natural and useful. Outputs an actionable, prioritized list of on-page SEO improvements.
Generates production-ready Kubernetes manifests — Deployments, Services, Ingresses, ConfigMaps, Secrets, HPAs, and more — from a plain-language description of the workload. Applies best practices for resource limits, health probes, security contexts, and rolling update strategies, with optional Kustomize overlays or Helm chart scaffolding.
Parses and analyzes application, system, and access logs to surface errors, anomalies, and root causes. Correlates events across services, identifies recurring patterns and spikes, extracts structured fields from unstructured lines, and produces a prioritized summary with likely causes and recommended next steps.
Designs GraphQL schemas from domain descriptions or existing data models. Produces typed SDL with queries, mutations, subscriptions, input types, enums, and interfaces, following naming conventions, pagination patterns (Relay-style connections), and error-handling best practices. Can also generate resolvers scaffolding and map schemas to existing REST or SQL backends.
Creates comprehensive design system documentation and component specifications from existing UI patterns or requirements. Generates design tokens, component APIs, usage guidelines, and accessibility specifications. Supports Figma-to-code workflows and produces consistent theming across platforms.
Generates and assists with incident response procedures for production systems. Helps with root cause analysis, creates runbooks for common failure modes, builds communication templates for stakeholders, and produces post-incident review documents. Supports SRE and on-call workflows.
Designs and generates data pipeline configurations for ETL/ELT workflows. Supports Apache Airflow DAGs, dbt models, Spark jobs, and streaming pipelines with Kafka or Flink. Creates data quality checks, schema evolution strategies, and monitoring dashboards for pipeline health.
Generates production-ready infrastructure as code (IaC) configurations for cloud deployments. Supports Terraform, Pulumi, CloudFormation, and CDK. Creates modular, reusable infrastructure components with proper networking, security groups, IAM policies, and monitoring configurations.
Generates comprehensive load testing scripts and configurations for APIs. Supports k6, Locust, Artillery, and JMeter formats. Creates realistic traffic patterns, ramp-up scenarios, and threshold definitions. Includes analysis templates for identifying bottlenecks and capacity planning.
Generates mobile application prototypes and implementations for iOS and Android. Creates SwiftUI views, Jetpack Compose layouts, and React Native components from descriptions or wireframe images. Handles navigation patterns, state management, and platform-specific design guidelines.
Performs systematic threat modeling for software systems using frameworks like STRIDE, PASTA, and Attack Trees. Identifies potential security threats, attack vectors, and vulnerabilities in system architectures. Produces prioritized risk assessments with mitigation strategies and security controls.
Performs a full App Store Optimization health check across 10 weighted dimensions: title, subtitle, keyword field, description, screenshots, preview video, ratings and reviews, icon, keyword rankings, and conversion signals. Produces a scored ASO report card (0–100) with quick wins, high-impact changes, and strategic recommendations prioritized by effort and expected impact.
Discovers, evaluates, and prioritizes App Store keywords for mobile apps. Expands seed keywords using autocomplete suggestions, competitor rankings, and category analysis, then scores each keyword by volume, difficulty, and relevance to build a prioritized keyword strategy with primary, secondary, long-tail, and aspirational buckets.
Performs a comprehensive competitive intelligence analysis for mobile apps on the App Store and Google Play. Compares metadata, keyword gaps, creative strategy (screenshots, preview video, icon), ratings, monetization, and growth signals across up to 5 competitors, then delivers a prioritized opportunity map with quick wins and strategic recommendations.
Crafts App Store metadata — title, subtitle, keyword field, and description — that maximizes both search visibility and conversion rate. Applies platform-specific character limits and indexing rules for iOS and Android, provides multiple copy variants per field, and outputs a keyword coverage matrix with before/after comparison.
Skills 与 MCP 服务器
有什么区别?Skills定义“做什么”
Skill 将说明、示例提示词和推荐模型组织在一起,让智能体稳定地完成任务。Skills 增加的是知识,而不是新的连接。
MCP 服务器定义“如何连接”
MCP 服务器通过连接数据库、API 和文件等真实系统,为智能体增加新能力。MCP 提供连接和操作,而不是任务说明。
简单来说:当模型需要把某项任务做好时选择 Skill;当模型需要访问工具或系统时选择 MCP 服务器。两者可以组合使用,Skill 可以依赖 MCP 服务器提供的工具。
创建了实用的 Skill?
提交 SKILL.md,加入由社区维护的开源注册表。