Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Use for framework-gated self-evolve workflows in AWorld: evolve skills, create trajectory-backed proposals, inspect self-evolve run artifacts, run aworld-cli optimize, or prepare verified apply decisions through aworld.self_evolve gates.
Creates new agents from user requirements by generating Python implementation and mcp_config.
Update Tool Capability
ClawSkillsHub Skill Manager - Search and install skills from the ClawSkillHub registry.
Add a new deterministic scoring check in src/scoring/checks/ that evaluates config quality. Follows the Check[] return pattern, uses point constants from src/scoring/constants.ts, and integrates via filterChecksForTarget() in src/scoring/index.ts. Use when user says 'add scoring check', 'new check', 'modify scoring criteria', or works in src/scoring/checks/. Do NOT use for display changes or refactoring scoring logic.
Add a new platform writer module in src/writers/ that generates and writes agent config files for a supported platform. Each writer exports a function that accepts a config interface, creates directories (rules/, skills/, mcp configs), writes files with proper formatting and frontmatter, and returns string[] of written file paths. Use when adding platform support for a new agent, integrating a new code AI tool, or extending caliber to support new targets. Do NOT use for modifying existing writers, refactoring scoring logic, or changing how writers are invoked.
Add or modify an AI chat tool ("Ask Ryo" capability) in ryOS. Covers the server-side tool definition (Zod schema + description + optional execute) and the client-side handler dispatch, plus the server-vs-client execution split. Use when giving the AI a new capability, adding a tool to the chat agent, or editing chat/tool schemas, descriptions, or handlers.
Answer 'how do I use X / where is setting Y / what does panel Z do' questions about Hope Agent from the built-in bilingual user guide instead of guessing from memory. Trigger on: 怎么用, 在哪设置, 怎么开启, 如何配置, 使用手册, 用户手册, 功能说明, how to use, where is the setting, how do I enable, user guide, manual. The guide covers install & onboarding, models & providers, chat & sessions, memory, knowledge space, design space, tools & permissions, autonomous tasks, multi-agent & cron, IM channels, MCP/hooks/skills, projects & insights, settings & security. NOT for: internal implementation questions (ha-self-diagnosis), error/log investigation (ha-logs), actually changing settings (ha-settings).
Specify the safety and reliability guardrails for an LLM feature before it ships. Use when asked to define LLM guardrails, add safety controls to an AI feature, prevent prompt injection or jailbreaks, or harden a chatbot/agent against misuse. Produces a guardrails spec — threats, input/output controls, refusal and escalation policy, logging, and a red-team test set — mapped to where each control runs.
Update the agent knowledge base after making code changes in the Roslyn repo. Run at the end of every task that modifies code, adds files, changes public APIs or diagnostics, or establishes new patterns. Keeps .github/memory/ fresh and reliable.