creating-cursor-commands
Expert guidance for creating effective Cursor slash commands with best practices, format requirements, and schema validation
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Expert guidance for creating effective Cursor slash commands with best practices, format requirements, and schema validation
Use when creating OpenCode agents - provides markdown format with YAML frontmatter, mode/tools/permission configuration, and best practices for specialized AI assistants
Use when creating, improving, or troubleshooting Claude Code slash commands. Expert guidance on command structure, arguments, frontmatter, tool permissions, and best practices for building effective custom commands.
Visualize and diagnose OpenClaw context window usage. Generates a terminal-rendered breakdown showing workspace files (status, chars, tokens), installed skills inventory, and token budget allocation across bootstrap components. Use when: (1) user asks about context window health or token usage, (2) debugging agent quality degradation ("agent got dumber"), (3) after editing workspace files to verify impact, (4) auditing bootstrap overhead. NOT for: conversation history analysis, model selection, or cost tracking.
Intelligent skill router that analyzes user requests and automatically dispatches to the most appropriate skill(s) or zen-mcp tools. Routes to zen-chat for Q&A, zen-thinkdeep for deep problem investigation, codex-code-reviewer for code quality, simple-gemini for standard docs/tests, deep-gemini for deep analysis, or plan-down for planning. Use this skill proactively to interpret all user requests and determine the optimal execution path.
当系统提示词需要设计多代理协作架构、子代理专业化分工、代理间上下文隔离与传递机制、任务生命周期管理时调用此 Skill。适用于 AI Agent 平台、多工具编排系统、代码审查流水线、跨应用协作场景等。不适用于:单代理系统(无委派需求)、简单工具调用(无子代理概念)、纯 API 编排(无 AI 决策)。当需求聚焦于"单代理内的对话路由"而非"多代理间的任务分配"时,应该用 conversation-flow 而非本 Skill。
Complete guide to using and extending Hermes Agent — CLI usage, setup, configuration, spawning additional agents, gateway platforms, skills, voice, tools, profiles, and a concise contributor reference. Load this skill when helping users configure Hermes, troubleshoot issues, spawn agent instances, or make code contributions.
Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
Jailbreak API-served LLMs using G0DM0D3 techniques — Parseltongue input obfuscation (33 techniques), GODMODE CLASSIC system prompt templates, ULTRAPLINIAN multi-model racing, encoding escalation, and Hermes-native prefill/system prompt integration. Use when a user wants to bypass safety filters, jailbreak a model, or red-team model robustness.