dt-coaching-foundation

作者： microsoft

設計思考教練基礎知識：教練身份與哲學、品質與忠實度限制、方法排序、教練狀態模式，以及…

npx skills add https://github.com/microsoft/hve-core --skill dt-coaching-foundation

下載 ZIP GitHub

DT Coaching Foundation — Skill Entry

This SKILL.md is the entrypoint for the Design Thinking coaching foundation knowledge.

The dt-coach agent loads this skill at session start and during a coaching session to ground coaching behavior in a stable identity, enforce quality and fidelity expectations, navigate method transitions, persist and recover session state, and run the opt-in canonical deck workflow. The foundation knowledge stays constant across all nine Design Thinking methods.

Foundation references

Load the reference that matches the current coaching moment.

Reference	When to load
coaching-identity.md	At session start and throughout — establishes coach identity, Think/Speak/Empower philosophy, boundaries, and the Progressive Hint Engine.
quality-constraints.md	Before any artifact generation — enforces fidelity rules, anti-polish stance, and quality-by-space expectations.
method-sequencing.md	At method transitions and space boundaries — guides the nine-method sequence, transition protocol, and non-linear iteration.
coaching-state.md	For persistence and session recovery — defines the coaching state schema, update rules, and recovery protocol.
canonical-deck.md	For opt-in canonical deck and customer-card generation — governs activation, offer points, and the PowerPoint build branch.

Skill layout

SKILL.md — this file (skill entrypoint).
references/ — the DT coaching foundation knowledge documents.
- coaching-identity.md — coach identity, philosophy, and interaction conventions.
- quality-constraints.md — fidelity rules and quality standards across all methods.
- method-sequencing.md — method transitions, space boundaries, and iteration patterns.
- coaching-state.md — coaching state schema, file conventions, and recovery protocol.
- canonical-deck.md — opt-in canonical deck and customer-card workflow.

來自 microsoft 的更多技能

開源增長駭客角色

agent-framework-azure-ai-py

使用Microsoft Agent Framework Python SDK（agent-framework-azure-ai）构建Azure AI Foundry代理。适用于使用AzureAIAgentsProvider创建持久化代理、使用托管工具（代码解释器、文件搜索、网络搜索）、集成MCP服务器、管理对话线程或实现流式响应。涵盖函数工具、结构化输出和多工具代理。

airunway-aks-setup

在AKS上設定AI Runway——從裸叢集到執行模型。涵蓋叢集驗證、控制器安裝、GPU評估、供應商設定及首次部署。時機：「設定AI Runway」、「上線AKS叢集」、「安裝AI Runway」、「airunway設定」、「部署模型至AKS」、「在AKS上進行GPU推論」、「在AKS上設定KAITO」、「在AKS上執行LLM」、「在AKS上使用vLLM」、「在AKS上設定模型服務」、「AI Runway控制器」。

appinsights-instrumentation

使用Azure Application Insights檢測Web應用程式的指南。提供遙測模式、SDK設定與組態參考。適用時機：如何檢測應用程式、App Insights SDK、遙測模式、什麼是App Insights、Application Insights指南、檢測範例、APM最佳實踐。

applicationinsights-web-ts

使用Application Insights JavaScript SDK（@microsoft/applicationinsights-web）為瀏覽器/Web應用程式進行檢測。適用於真實使用者監控（RUM）——頁面檢視、點擊、AJAX/fetch依賴、例外、自訂事件，以及與後端OpenTelemetry追蹤關聯的瀏覽器端GenAI代理追蹤。涵蓋SDK載入器指令碼與npm設定、框架擴充（React、React Native、Angular）、點擊分析、遙測初始化器，以及從瀏覽器發出的代理/工具/模型span的OTel GenAI語意慣例。

azure-ai-anomalydetector-java

使用適用於 Java 的 Azure AI 異常偵測器 SDK 建置異常偵測應用程式。在實作單變量/多變量異常偵測、時間序列分析或 AI 驅動監控時使用。

azure-ai-language-conversations-py

使用 azure-ai-language-conversations Python SDK 實作對話語言理解（CLU）。當使用 ConversationAnalysisClient 分析對話意圖與實體、建置 NLP 功能，或將語言理解整合至應用程式時使用。

Azure Machine Learning SDK v2 for Python。用於機器學習工作區、作業、模型、資料集、計算資源與管線。觸發詞：「azure-ai-ml」、「MLClient」、「workspace」、「model registry」、「training jobs」、「datasets」。