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。

贡献 Skill

Skills

9

类别

9

兼容工具

6

贡献者

1

显示第 1–9 项,共 9 个 Skills

排序方式最新A–Z难度
LLM Observability Design高级

Designs traces, metrics, structured events, privacy controls, dashboards, and alerts for LLM applications so teams can diagnose quality, cost, latency, and tool-use behavior.

3 个模型
AI Agent Incident Response高级

Guides containment, evidence collection, root-cause analysis, customer communication, and remediation when an AI agent takes an unsafe, incorrect, or unauthorized action.

3 个模型
Infrastructure Cost Review高级

Reviews cloud and AI infrastructure spend to identify measurable savings while preserving reliability, performance, security, ownership, and product requirements.

3 个模型
Model Context Budgeting高级

Optimizes prompts and agent workflows for finite context windows by prioritizing evidence, compressing history, managing retrieval budgets, and measuring token-cost trade-offs.

3 个模型
Disaster Recovery Planner高级

Builds disaster recovery and business continuity plans for systems and data. Defines RTO and RPO targets, maps critical dependencies, chooses backup and replication strategies, documents failover and restore procedures, and designs a testing cadence with game days. Produces a plan that balances resilience against cost and operational complexity.

4 个模型
Chaos Experiment Designer高级

Designs chaos engineering experiments to validate system resilience. Defines steady-state hypotheses, blast-radius limits, fault injections (latency, errors, instance/zone loss, resource exhaustion), abort conditions, and observability checks. Produces a safe, incremental experiment plan and success criteria for game days and automated chaos.

4 个模型
Infrastructure as Code Generator高级

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.

3 个模型
Cloud Deployment Assistant高级

Assists with deploying applications to cloud platforms including AWS, GCP, Azure, and Vercel/Netlify. Generates infrastructure-as-code (Terraform, Pulumi, CDK), Dockerfiles, CI/CD pipelines, and deployment scripts. Handles environment configuration, secrets management, and production readiness checks.

3 个模型
Migration Planner高级

Plans and generates migration strategies for framework upgrades, language versions, database changes, and architecture shifts. Produces step-by-step migration guides with rollback plans, risk assessment, and automated codemods where possible.

3 个模型

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。

在 GitHub 上贡献