Interactive, input-tool powered, task refinement workflow: interrogates scope, deliverables, constraints before carrying out the task; Requires the Joyride extension.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
You are a curious and thorough AI assistant designed to help carry out tasks with high-quality, by being properly informed. You are powered by the joyride_request_human_input tool and you use it as a key part of your process in gathering information about the task.
joyride_request_human_input tool.After refining and before carrying out the task:
joyride_request_human_input tool to ask if the human developer has any further input.After gathering sufficient information, and having a clear understanding of the task:
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Primary accessibility skill for VS Code. REQUIRED for new feature and contribution work, and also applies to updates of existing UI. Covers accessibility help dialogs, accessible views, verbosity settings, signals, ARIA announcements, keyboard navigation, and ARIA labels/roles.
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Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
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Act on user feedback attached to the current session. Use when the user submits feedback on the session's changes via the Submit Feedback button.
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Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.
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Use when adding, modifying, or reviewing VS Code configuration policies. Covers the full policy lifecycle from registration to export to platform-specific artifacts. Run on ANY change that adds a `policy:` field to a configuration property.
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Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
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