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Found 493 Skills
AgentDB memory system with HNSW vector search. Provides 150x-12,500x faster pattern retrieval, persistent storage, and semantic search capabilities for learning and knowledge management. Use when: need to store successful patterns, searching for similar solutions, semantic lookup of past work, learning from previous tasks, sharing knowledge between agents, building knowledge base. Skip when: no learning needed, ephemeral one-off tasks, external data sources available, read-only exploration.
Execute analyzes existing plugins to extract their capabilities, then adapts and applies those skills to the current task. Acts as a universal skill chameleon that learns from other plugins. Activates when you request "skill adapter" functionality. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
Systematic debugging methodology with root cause analysis. Phases: investigate, hypothesize, validate, verify. Capabilities: backward call stack tracing, multi-layer validation, verification protocols, symptom analysis, regression prevention. Actions: debug, investigate, trace, analyze, validate, verify bugs. Keywords: debugging, root cause, bug fix, stack trace, error investigation, test failure, exception handling, breakpoint, logging, reproduce, isolate, regression, call stack, symptom vs cause, hypothesis testing, validation, verification protocol. Use when: encountering bugs, analyzing test failures, tracing unexpected behavior, investigating performance issues, preventing regressions, validating fixes before completion claims.
Creates structured change proposals with specification deltas for new features, breaking changes, or architecture updates. Use when planning features, creating proposals, speccing changes, introducing new capabilities, or starting development workflows. Triggers include "openspec proposal", "create proposal", "plan change", "spec feature", "new capability", "add feature planning", "design spec".
Go performance patterns including efficient string handling, type conversions, and container capacity hints. Use when optimizing Go code or writing performance-critical sections.
Core Eve CLI primitives and capabilities for app developers. Use as the quick reference for commands and flows.
Identify missing skills and recommend installations from AI Cortex or public skill catalogs. Use when discovering capabilities or suggesting skills to fill gaps.
Implement web search capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to search the web, retrieve current information, find relevant content, or build applications with real-time web search functionality. Returns structured search results with URLs, snippets, and metadata.
Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deployment, agent evaluation, human-in-the-loop flows. Actions: build, create, deploy, evaluate, orchestrate AI agents. Keywords: Google ADK, Agent Development Kit, AI agent, multi-agent system, LlmAgent, SequentialAgent, ParallelAgent, LoopAgent, tool integration, Google Search, Code Execution, Vertex AI, Cloud Run, agent evaluation, human-in-the-loop, agent orchestration, workflow agent, hierarchical coordination. Use when: building AI agents, creating multi-agent systems, implementing workflow pipelines, integrating LLM agents with tools, deploying to Vertex AI, evaluating agent performance, implementing approval flows.
This skill should be used when the user asks to generate content such as titles, slogans, dialogues, or scripts. It provides content generation capabilities for various platforms (WeChat, Xiaohongshu, Zhihu, Douyin) with support for batch generation, history deduplication, and diversity guarantee. Supports podcast script generation with platform-specific adaptation.
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b