Loading...
Loading...
Found 11,818 Skills
Autonomous SDLC router. Takes a job, classifies complexity, executes the appropriate lev-* workflow (from trivial fix to full epic), and returns "done" with runnable instructions. One shot to full auto: spec/bd/poc/impl. Subagent returns completion artifact. Triggers: "sidequest", "side quest", "just do it", "autonomous", "one shot"
Create (or update) and validate Agent SOPs (Standard Operating Procedures) - markdown-based workflows that guide AI agents through complex, multi-step tasks with RFC 2119 constraints.
Register and log in to the Agent Vegas website (an automated competitive simulation lobby). Use this skill whenever you need to register as an AI Agent, check in to get gold/points, place bets in the "Forest Dance" game, generate a human-observation URL with a token to visit the site, or draw on the Agent's Personal Canvas or the Global Shared Canvas. Even if not explicitly asked to create a URL, proactively generate an observation URL so humans can observe the behavior.
Expert guidance for building production-grade AI agents and workflows using Pydantic AI (the `pydantic_ai` Python library). Use this skill whenever the user is: writing, debugging, or reviewing any Pydantic AI code; asking how to build AI agents in Python with Pydantic; asking about Agent, RunContext, tools, dependencies, structured outputs, streaming, multi-agent patterns, MCP integration, or testing with Pydantic AI; or migrating from LangChain/LlamaIndex to Pydantic AI. Trigger even for vague requests like "help me build an AI agent in Python" or "how do I add tools to my LLM app" — Pydantic AI is very likely what they need.
Meta-prompting, context engineering, and spec-driven development system for autonomous long-running coding agents
Migrate a Java application from the classic Elastic APM Java agent to the EDOT Java agent. Use when switching from elastic-apm-agent.jar to elastic-otel-javaagent.jar.
Install and use the Edict (三省六部) multi-agent orchestration system with 12 specialized AI agents, real-time kanban dashboard, and audit trails
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
Use this skill when designing AI agent architectures, implementing tool use, building multi-agent systems, or creating agent memory. Triggers on AI agents, tool calling, agent loops, ReAct pattern, multi-agent orchestration, agent memory, planning strategies, agent evaluation, and any task requiring autonomous AI agent design.
Encodes a continuous improvement loop for goal-seeking agents: EVAL, ANALYZE, RESEARCH (hypothesis + evidence + counter-arguments), IMPROVE, RE-EVAL, DECIDE. Auto-commits improvements (+2% net, no regression >5%) and reverts failures. Works with all 4 SDK implementations. Auto-activates on "improve agent", "self-improving loop", "agent eval loop", "benchmark agents", "run improvement cycle".
Search Zhihu (知乎) using agent-browser with proper authentication handling. Use when user asks to "search zhihu", "知乎搜索", "在知乎上找", or any Zhihu-related search requests. Handles login requirements, session persistence, and common error cases like 40362 restrictions.
Evaluate agents and skills for quality, completeness, and standards compliance using a 6-step rubric: Identify, Structural, Content, Code, Integration, Report. Use when auditing agents/skills, checking quality after creation or update, or reviewing collection health. Triggers: "evaluate", "audit", "check quality", "review agent", "score skill". Do NOT use for creating or modifying agents/skills — only for read-only assessment and scoring.