rpi-research
Research-only RPI playbook that gathers task evidence, writes dated research artifacts under .copilot-tracking/research/, and hands off planning-ready findings. Use when the user needs evidence, alternatives, or task framing first.
556 skills
Research-only RPI playbook that gathers task evidence, writes dated research artifacts under .copilot-tracking/research/, and hands off planning-ready findings. Use when the user needs evidence, alternatives, or task framing first.
Compatibility alias for behavior-preserving prompt artifact cleanup. Routes refactoring to hve-builder refactor mode.
Compatibility alias for legacy prompt-building requests. Routes creation and improvement to the hve-builder skill.
Compatibility alias for read-only prompt artifact review. Routes static and behavior analysis to hve-builder review mode.
Create, improve, refactor, replace, review, or validate prompts, instructions, agents, subagents, and skills. Use for Copilot customization cleanup, extending HVE workflows with project-specific capabilities, and parent-owned correction of material review or behavior-test findings.
Assess a frozen prompt, instruction, agent, subagent, or skill through black-box behavior testing with explicit fidelity and independent grading. Use for hve-builder candidate assessment and reassessment after corrections, or to test an existing artifact without editing it.
Set up GitHub Copilot OpenTelemetry capture: configure the VS Code export settings, generate a local Grafana stack and dashboard, or generate the Azure collector, infrastructure, and dashboard for an organization.
Create and validate HVE Core agents, prompts, instructions, and skills with current frontmatter, package membership, delegation, tracking, documentation, and validation conventions. Use when authoring a GitHub Copilot customization artifact in this repository.
How to record project learnings so that later-phase workers and future agent runs can consume them.
Discovers valid migration plans in the workspace and returns the selected plan path. A valid plan is a subdirectory of .github/modernize/ that contains plan.md AND tasks.json (tasks.json may be in the plan folder or in a .metadata subfolder). Handles 0, 1, or multiple plans and prompts the user when a choice is needed. Triggers: "list plans", "find plans", "select plan", "list-and-select-plan", "discover plans".
Evaluates whether a user's modernization/rewrite request provides enough scenario context to proceed (e.g., target component library, screenshots, design system for frontend; API contract policy, data migration strategy for backend). Produces a deterministic clarity score, asks the user for missing required fields via a structured form, and writes a canonical `clarification.md` artifact consumed by all downstream agents. Triggers: "clarification gate", "scenario clarification", "elicit missing context", "evaluate prompt completeness", "ask user for screenshots / target library / design system"
Build agentic applications with GitHub Copilot SDK. Use when embedding AI agents in apps, creating custom tools, implementing streaming responses, managing sessions, connecting to MCP servers, or creating custom agents. Triggers on Copilot SDK, GitHub SDK, agentic app, embed Copilot, programmable agent, MCP server, custom agent.
Trigger ADO pipelines for a Copilot-created PR by posting /azp run comments. Use when the user asks to trigger CI pipelines for a specific PR.
Development workflow for building, syncing, packaging, and shipping Copilot Studio agents. Use this skill when working with Copilot Studio YAML files (agent.mcs.yml, topics, actions, variables), when pulling or pushing agent changes, when packaging solutions for distribution, or when troubleshooting common Copilot Studio platform issues. Triggers on: Copilot Studio, MCS, agent.mcs.yml, .mcs.yml files, pac CLI, Power Platform solution, pull from cloud, push to cloud, publish agent, solution packaging, heartbeat flow, Power Automate flows.
Use this skill when the user's Copilot Studio agent evaluations have come back and they need to interpret scores, diagnose root causes of underperforming test cases, find remediation steps, or analyze patterns to improve their agent. Always use this skill when the user mentions: "eval failed", "why did this fail", "triage", "diagnose failure", "low pass rate", "fix evaluation results", "not passing", "failing test cases", "evaluation results", "improve my eval scores", or any situation where eval scores need interpretation and action.
Analyzes Copilot Studio evaluation results using Practical Guidance on Agent Evaluation's 10-step playbook (Steps 6, 7, and 9) plus Microsoft's triage diagnostics. Returns a gate-based SHIP / ITERATE / BLOCK verdict with root cause classification, remediation, and pattern analysis.
服务端路径安全与文件访问编码规范。在编写文件下载路由、Agent 工具(文件读取/目录列出)、数据连接器/Loader、Workspace 路径操作、沙箱配置时使用。
LLM Agent 多语言注入规范。在修改 Agent 提示词、添加新的 Agent 端点、处理用户可见的后端消息(message_code)时使用。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Validate, run, and execute workflows; creating new workflows when explicitly asked. Use when orchestrating AI agents via YAML workflow files, executing an existing workflow, debugging execution, configuring routing between agents, setting up human-in-the-loop gates, or understanding workflow YAML schema. Only create new workflows when explicitly asked.
Use this skill when the user asks to create, improve, review, package, genericise, or submit an Agent Skill, SKILL.md file, skill metadata, or reusable agent instruction bundle.
Use this skill when the user needs to choose the right Microsoft AI platform for a project, is comparing Microsoft 365 Copilot, Agent Builder, Copilot Studio, Microsoft Foundry, Foundry Agent Service, Windows AI Foundry, or Agent 365, needs to gather requirements for an AI or agent build, needs a solution architecture recommendation, needs to estimate effort as technical complexity and risk, or asks any variant of "which platform should I use", "how do I choose", "help me scope this AI project", or "what's the right tool for this AI use case".
Use this skill whenever the user wants to search, browse, or look up records in a Microsoft Dataverse table — for example "look up accounts", "find opportunities for Contoso", "show me contact details", or "search cases by status". Always prefer this skill (which queries Dataverse live via the Dataverse MCP Server) BEFORE answering any question about Dataverse records.