ReddRadar
Topic: openrouter
53 skills in this topic.
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V3 Deep Integration
Deep agentic-flow@alpha integration implementing ADR-001. Eliminates 10,000+ duplicate lines by building claude-flow as specialized extension rather than parallel implementation.
ruvnet/agentic-flow 607
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V3 Core Implementation
Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.
ruvnet/agentic-flow 607
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stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
ruvnet/agentic-flow 607
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sparc-methodology
SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
ruvnet/agentic-flow 607
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Pair Programming
AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
ruvnet/agentic-flow 607
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Hooks Automation
Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.
ruvnet/agentic-flow 607
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github-workflow-automation
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
ruvnet/agentic-flow 607
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AgentDB Memory Patterns
Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
ruvnet/agentic-flow 607
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agentic-jujutsu
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
ruvnet/agentic-flow 607
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flow-nexus-neural
Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
ruvnet/agentic-flow 607
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flow-nexus-platform
Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges
ruvnet/agentic-flow 607
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github-multi-repo
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
ruvnet/agentic-flow 607
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hive-mind-advanced
Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory
ruvnet/agentic-flow 607
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frontend
Rules and best practices when working on the dashboard and elements React frontend codebases
speakeasy-api/gram 227
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golang
Rules and best practices when writing and editing Go (Golang) code
speakeasy-api/gram 227
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vercel-react-best-practices
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
speakeasy-api/gram 227
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datadog
Use Datadog MCP tools to investigate logs, metrics, traces, and incidents for the Gram project. Activate when the user asks about errors, performance issues, incidents, latency, or wants to search telemetry data.
speakeasy-api/gram 227
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clickhouse
Rules when working with ClickHouse database in Gram for analytics and telemetry features
speakeasy-api/gram 227
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gram-functions
A walkthrough of the Gram Functions feature in this codebase
speakeasy-api/gram 227
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postgresql
Rules when working with PostgreSQL database in Gram
speakeasy-api/gram 227
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mise-tasks
Rules and best practices for writing and editing mise tasks.
speakeasy-api/gram 227
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datadog-insights
Investigate Gram production health and post a digest to Slack
speakeasy-api/gram 227
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smart-docs
AI-powered comprehensive codebase documentation generator. Analyzes project structure, identifies architecture patterns, creates C4 model diagrams, and generates professional technical documentation. Use when users need to document codebases, understand software architecture, create technical specs, or generate developer guides. Supports all programming languages. Alternative to Litho/deepwiki-rs that uses Claude Code subscription without external API costs.
sopaco/deepwiki-rs 858
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deepwiki-rs
AI-powered Rust documentation generation engine for comprehensive codebase analysis, C4 architecture diagrams, and automated technical documentation. Use when Claude needs to analyze source code, understand software architecture, generate technical specs, or create professional documentation from any programming language.
sopaco/deepwiki-rs 858