Inference1

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Ascend Inference Repos Copilot · inference1
专用于以下昇腾（Ascend）推理开源代码仓库的智能问答技能：vLLM、vLLM-Ascend、MindIE-LLM、MindIE-SD、MindIE-Motor、MindIE-PyMotor、MindIE-Turbo 以及 msModelSlim (MindStudio-ModelSlim)。当回答用户关于前述代码仓的问题时，需提供因果链感知、基于证据的技术回答，并确保回答完整、准确、逻辑合理且可追溯。覆盖的技术问题包括但不限于：源码理解、软件架构、部署与使用步骤指引、API 和参数配置、模型与特性支持查询、模型量化后如何推理、调试技巧、测试验证、故障排除与解决、日志异常检测、性能优化、精度验证、定制开发以及其他相关技术问题。支持中英文双语回复，还可以借助 DeepWiki MCP 工具，对仓库中的信息进行更深入的检索。触发条件（满足以下任意一项即可）：1. 用户的问题中提及上述任一仓库名称（支持中英文别名，且不区分大小写）；2. 用户的问题中同时包含 "昇腾推理" 或 "Ascend Inference"，并且涉及大模型、多模态、部署、性能、报错或代码等相关信息。Use this skill whenever the user asks about vLLM on Ascend/NPU hardware, MindIE components, ModelSlim quantization, or any Huawei Ascend inference stack — even if they don't explicitly name a repository.

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Clarify Intent And Establish Shared Understanding · inference1 bundle
Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understan

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