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Found 5,789 Skills
(Industry standard: Sequential Agent / Agent as a Tool) Primary Use Case: Delegating a well-defined task to a worker agent, verifying its execution, and repeating if necessary. Inner/outer agent delegation pattern. Use when: work needs to be delegated from a strategic controller (Outer Loop) to a tactical executor (Inner Loop) via strategy packets, with verification and correction loops.
Create, synthesize, and iteratively improve agent skills following the Agent Skills specification. Use when asked to "create a skill", "write a skill", "synthesize sources into a skill", "improve a skill from positive/negative examples", "update a skill", or "maintain skill docs and registration". Handles source capture, depth gates, authoring, registration, and validation.
Defragment and reorganize agent memory files: split bloated files, merge duplicates, remove stale information, and restructure the memory hierarchy. Use when memory files have grown unwieldy, contain redundancies, or need reorganization. Run periodically (weekly) or on demand.
MUST READ before setting up observability for ADK agents or when analyzing production traffic, debugging agent behavior, or improving agent performance. ADK observability guide — Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations, and troubleshooting. Use when configuring monitoring, tracing, or logging for agents, or when understanding how a deployed agent handles real traffic.
MUST READ before writing or modifying ADK agent code. ADK API quick reference for Python — agent types, tool definitions, orchestration patterns, callbacks, and state management. Includes an index of all ADK documentation pages. Do NOT use for creating new projects (use adk-scaffold).
Save a concise handoff summary only when the user explicitly requests it. Use this for resumable progress notes in generic agent environments where a real session importer is not guaranteed.
AI-агент для управления Facebook рекламой. Вызывай для анализа, оптимизации, создания кампаний и отчётов.
Generates high-quality Gherkin (BDD) scenarios from functional requirements using a two-agent iterative cycle: a generator agent that creates/modifies the Gherkin and a reviewer agent that validates it and proposes improvements. The cycle repeats automatically until the Gherkin passes review. Use this skill whenever the user mentions: "generate Gherkin", "BDD scenarios", "Gherkin test cases", "Feature/Scenario/Given/When/Then", "requirements to Gherkin", "BDD specifications", or asks to transform functional requirements into behaviour tests. Also applies when the user brings a requirements document and wants test cases, acceptance criteria, or user stories with executable examples.
This skill is used when the user requests 'review my prompt', 'analyze my conversation history', 'diagnose my understanding level', or when it is invoked via /prompt-review. It reads past AI Agent conversation histories (Claude Code, GitHub Copilot Chat, Cline, Roo Code, Windsurf, Antigravity), estimates the user's technical understanding level, prompting patterns and AI dependency, then generates a corresponding report.
This skill should be used when the user asks to "set up agent todos", "initialize the todo store", "configure todos", "run todo init", "set up .agent-todos.local.json", or wants to set up or reconfigure the todo store for this project.
飞书 OAuth 认证和 User Access Token 管理。两步式非交互登录（AI Agent 专用）、 Token 状态检查、scope 配置、自动刷新机制、搜索功能的 Token 依赖关系。 当用户请求"登录飞书"、"获取 Token"、"OAuth 授权"、"auth login"、"认证"、 "搜索需要什么权限"、"Token 过期了"、"刷新 Token"时使用。 当遇到权限错误（如 99991679 Unauthorized）、Token 过期、state 不匹配等问题时也应使用此技能。 也适用于：搜索命令报权限错误、Token 相关的排错、需要判断当前授权状态的场景。 当其他飞书技能（toolkit/msg/read 等）遇到 User Access Token 相关问题时，也应参考此技能。
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