Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need through a file system paradigm, enabling hierarchical context delivery and self-evolving.
Hexagonal hierarchical geospatial indexing system
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
👽 Terraform Orchestration Tool for DevOps. Keep environment configuration DRY with hierarchical imports of configurations, inheritance, and WAY more. Native support for Terraform and Helmfile.
Python bindings for H3, a hierarchical hexagonal geospatial indexing system
DeepResearchAgent is a hierarchical multi-agent system designed not only for deep research tasks but also for general-purpose task solving. The framework leverages a top-level planning agent to coordinate multiple specialized lower-level agents, enabling automated task decomposition and efficient execution across diverse and complex domains.
Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).
[EMNLP'25 findings] This is the official repo for the paper, HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge.
Go bindings for H3, a hierarchical hexagonal geospatial indexing system
PostgreSQL bindings for H3, a hierarchical hexagonal geospatial indexing system
Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go. For a specific DI library, → See `samber/cc-skills-golang@golang-google-wire`, `samber/cc-skills-golang@golang-uber-dig`, `samber/cc-skills-golang@golang-uber-fx`, or `samber/cc-skills-golang@golang-samber-do` skills.
Java bindings for H3, a hierarchical hexagonal geospatial indexing system
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need through a file system paradigm, enabling hierarchical context delivery and self-evolving.
Hexagonal hierarchical geospatial indexing system
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
👽 Terraform Orchestration Tool for DevOps. Keep environment configuration DRY with hierarchical imports of configurations, inheritance, and WAY more. Native support for Terraform and Helmfile.
Python bindings for H3, a hierarchical hexagonal geospatial indexing system
DeepResearchAgent is a hierarchical multi-agent system designed not only for deep research tasks but also for general-purpose task solving. The framework leverages a top-level planning agent to coordinate multiple specialized lower-level agents, enabling automated task decomposition and efficient execution across diverse and complex domains.
Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).
[EMNLP'25 findings] This is the official repo for the paper, HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge.
Go bindings for H3, a hierarchical hexagonal geospatial indexing system
PostgreSQL bindings for H3, a hierarchical hexagonal geospatial indexing system
Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go. For a specific DI library, → See `samber/cc-skills-golang@golang-google-wire`, `samber/cc-skills-golang@golang-uber-dig`, `samber/cc-skills-golang@golang-uber-fx`, or `samber/cc-skills-golang@golang-samber-do` skills.
Java bindings for H3, a hierarchical hexagonal geospatial indexing system
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need through a file system paradigm, enabling hierarchical context delivery and self-evolving.
Hexagonal hierarchical geospatial indexing system
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
👽 Terraform Orchestration Tool for DevOps. Keep environment configuration DRY with hierarchical imports of configurations, inheritance, and WAY more. Native support for Terraform and Helmfile.
Python bindings for H3, a hierarchical hexagonal geospatial indexing system
DeepResearchAgent is a hierarchical multi-agent system designed not only for deep research tasks but also for general-purpose task solving. The framework leverages a top-level planning agent to coordinate multiple specialized lower-level agents, enabling automated task decomposition and efficient execution across diverse and complex domains.
Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).
[EMNLP'25 findings] This is the official repo for the paper, HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge.
Go bindings for H3, a hierarchical hexagonal geospatial indexing system
PostgreSQL bindings for H3, a hierarchical hexagonal geospatial indexing system
Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go. For a specific DI library, → See `samber/cc-skills-golang@golang-google-wire`, `samber/cc-skills-golang@golang-uber-dig`, `samber/cc-skills-golang@golang-uber-fx`, or `samber/cc-skills-golang@golang-samber-do` skills.
Java bindings for H3, a hierarchical hexagonal geospatial indexing system
Skill 디렉토리
모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.
OpenViking is an open-source context database designed specifically for AI Agents(such as openclaw). OpenViking unifies the management of context (memory, resources, and skills) that Agents need through a file system paradigm, enabling hierarchical context delivery and self-evolving.
Hexagonal hierarchical geospatial indexing system
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
👽 Terraform Orchestration Tool for DevOps. Keep environment configuration DRY with hierarchical imports of configurations, inheritance, and WAY more. Native support for Terraform and Helmfile.
Python bindings for H3, a hierarchical hexagonal geospatial indexing system
DeepResearchAgent is a hierarchical multi-agent system designed not only for deep research tasks but also for general-purpose task solving. The framework leverages a top-level planning agent to coordinate multiple specialized lower-level agents, enabling automated task decomposition and efficient execution across diverse and complex domains.
Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).
[EMNLP'25 findings] This is the official repo for the paper, HiRAG: Retrieval-Augmented Generation with Hierarchical Knowledge.
Go bindings for H3, a hierarchical hexagonal geospatial indexing system
PostgreSQL bindings for H3, a hierarchical hexagonal geospatial indexing system
Comprehensive guide for dependency injection (DI) in Golang. Covers why DI matters (testability, loose coupling, separation of concerns, lifecycle management), manual constructor injection, and DI library comparison (google/wire, uber-go/dig, uber-go/fx, samber/do). Use this skill when designing service architecture, setting up dependency injection, refactoring tightly coupled code, managing singletons or service factories, or when the user asks about inversion of control, service containers, or wiring dependencies in Go. For a specific DI library, → See `samber/cc-skills-golang@golang-google-wire`, `samber/cc-skills-golang@golang-uber-dig`, `samber/cc-skills-golang@golang-uber-fx`, or `samber/cc-skills-golang@golang-samber-do` skills.
Java bindings for H3, a hierarchical hexagonal geospatial indexing system