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adebold AI Skills

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浏览 adebold 维护的已发布 AI 技能,比较用途与说明,并通过来源仓库了解安装方式。

作者统计

已收录技能

26

收录技能的仓库 Stars 合计

0

仓库 Forks

0

平均每个技能的仓库 Stars

0

同一仓库中的多个技能可能共享 Stars,合计包含重复仓库数据。

26 个技能

全部技能

GitHub

reasoningbank-intelligence

adebold

Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cogn...

GitHub

agentdb-performance-optimization

adebold

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling t...

GitHub

pair-programming

adebold

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. Fe...

GitHub

agentic-jujutsu

adebold

Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

GitHub

agentdb-advanced-features

adebold

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems,...

GitHub

swarm-orchestration

adebold

Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building d...

GitHub

hooks-automation

adebold

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,...

GitHub

swarm-advanced

adebold

Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows

GitHub

reasoningbank-with-agentdb

adebold

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learnin...

GitHub

github-release-management

adebold

Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

GitHub

sparc-methodology

adebold

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

GitHub

stream-chain

adebold

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

GitHub

hive-mind-advanced

adebold

Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory

GitHub

agentdb-learning-plugins

adebold

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, impleme...

GitHub

skill-builder

adebold

Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill...

GitHub

agentdb-memory-patterns

adebold

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 intell...

GitHub

verification-quality-assurance

adebold

Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

GitHub

flow-nexus-platform

adebold

Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges

默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。