llm-ai
90
agent-swarm-workflow
Jeffrey Emanuel's multi-agent implementation workflow using NTM, Agent Mail, Beads, and BV. The execution phase that follows planning and bead creation. Includes exact prompts used.
aiskillstore
data-ai
sorting
stars
current ordering strategy
query
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llm-ai
90
r-development
Modern R development practices emphasizing tidyverse patterns (dplyr 1.1 and later, native pipe, join_by, .by grouping), rlang metaprogramming, performance optimization, and package development. Use when Claude needs to write R code, create R packages, optimize R performance, or provide R programming guidance.
aiskillstore
data-ai
llm-ai
90
codeconscious-identity
CodeConscious认知主体性AI助手的核心身份定义和操作命令系统，提供/runtime.*系列命令用于探索、学习、思考、规划和执行，支持宪法治理和记忆管理
aiskillstore
data-ai
llm-ai
90
control-loop-extraction
Extract and analyze agent reasoning loops, step functions, and termination conditions. Use when needing to (1) understand how an agent framework implements reasoning (ReAct, Plan-and-Solve, Reflection, etc.), (2) locate the core decision-making logic, (3) analyze loop mechanics and termination conditions, (4) document the step-by-step execution flow of an agent, or (5) compare reasoning patterns across frameworks.
aiskillstore
data-ai
llm-ai
90
spawn-parallel
Pattern for spawning parallel subagents efficiently. Use when you need multiple independent tasks done concurrently.
aiskillstore
data-ai
llm-ai
90
memory-systems
Design and implement memory architectures for agent systems. Use when building agents that need to persist state across sessions, maintain entity consistency, or reason over structured knowledge.
aiskillstore
data-ai
llm-ai
90
dispatching-parallel-agents
Use when facing 3+ independent failures that can be investigated without shared state or dependencies - dispatches multiple Claude agents to investigate and fix independent problems concurrently
aiskillstore
data-ai
llm-ai
90
context-degradation
Recognize, diagnose, and mitigate patterns of context degradation in agent systems. Use when context grows large, agent performance degrades unexpectedly, or debugging agent failures.
aiskillstore
data-ai
llm-ai
90
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.
aiskillstore
data-ai
llm-ai
90
mcp-patterns
Model Context Protocol (MCP) server patterns for building integrations with Claude Code. Triggers on: mcp server, model context protocol, tool handler, mcp resource, mcp tool.
aiskillstore
data-ai
llm-ai
90
subagent-orchestration
This skill should be used when coordinating multiple subagents, implementing orchestrator patterns, or managing parallel agent workflows. Trigger phrases: "orchestrate agents", "coordinate subagents", "parallel agents", "multi-agent workflow", "delegate to agents", "run agents in parallel", "launch multiple agents".
aiskillstore
data-ai
llm-ai
90
dspy-agent-framework-integration
Comprehensive guide to integrating DSPy with Microsoft Agent Framework in AgenticFleet, covering typed signatures, assertions, routing cache, GEPA optimization, and agent handoffs.
Qredence
data-ai
llm-ai
90
context-fundamentals
Understand the components, mechanics, and constraints of context in agent systems. Use when designing agent architectures, debugging context-related failures, or optimizing context usage.
aiskillstore
data-ai
llm-ai
90
prompt-template-designer
Design reusable prompt templates that encode domain-specific patterns for recurring AI tasks. Use when you've executed similar prompts 2+ times and need to capture the pattern as reusable intelligence. NOT for one-off prompts or generic "ask AI a question" patterns.
aiskillstore
data-ai
llm-ai
90
creating-skills
Guides creation of effective Agent Skills with proper structure and validation. Use when users want to create a new skill, update an existing skill, or need guidance on skill design patterns, SKILL.md format, or verify.py implementation. NOT when just using existing skills (use those skills directly).
aiskillstore
data-ai
llm-ai
90
fiftyone-dataset-import
Universal dataset import for FiftyOne supporting all media types (images, videos, point clouds, 3D scenes), all label formats (COCO, YOLO, VOC, CVAT, KITTI, etc.), and multimodal grouped datasets. Use when users want to import any dataset regardless of format, automatically detect folder structure, handle autonomous driving data with multiple cameras and LiDAR, or create grouped datasets from multimodal data. Requires FiftyOne MCP server.
aiskillstore
data-ai
llm-ai
90
when-analyzing-performance-use-performance-analysis
Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms
aiskillstore
data-ai
llm-ai
90
ai-runtime-toolkit
AI Runtime工具装备系统，支持8个内部专业工具和10+个外部CLI工具的整合管理，提供工具发现、执行和配置功能，遵循整合优于创造的设计理念
aiskillstore
data-ai
llm-ai
90
using-superpowers
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Read tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
aiskillstore
data-ai
llm-ai
90
prompt-engineering
Advanced prompt engineering techniques for optimal AI responses. Use this when crafting prompts, optimizing AI interactions, or designing system prompts for applications.
aiskillstore
data-ai
llm-ai
90
harness-model-protocol
Analyze the protocol layer between agent harness and LLM model. Use when (1) understanding message wire formats and API contracts, (2) examining tool call encoding/decoding mechanisms, (3) evaluating streaming protocols and partial response handling, (4) identifying agentic chat primitives (system prompts, scratchpads, interrupts), (5) comparing multi-provider abstraction strategies, or (6) understanding how frameworks translate between native LLM APIs and internal representations.
aiskillstore
data-ai
llm-ai
90
context-optimization
Apply optimization techniques to extend effective context capacity. Use when context limits constrain agent performance, when optimizing for cost or latency, or when implementing long-running agent systems.
aiskillstore
data-ai
llm-ai
90
memory-system
Complete guide to the AgenticFleet memory system. Read this first.
Qredence
data-ai