Instrument a webapp to send useful telemetry data to Azure App Insights
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
This skill enables sending telemetry data of a webapp to Azure App Insights for better observability of the app's health.
Use this skill when the user wants to enable telemetry for their webapp.
The app in the workspace must be one of these kinds
Find out the (programming language, application framework, hosting) tuple of the application the user is trying to add telemetry support in. This determines how the application can be instrumented. Read the source code to make an educated guess. Confirm with the user on anything you don't know. You must always ask the user where the application is hosted (e.g. on a personal computer, in an Azure App Service as code, in an Azure App Service as container, in an Azure Container App, etc.).
If the app is a C# ASP.NET Core app hosted in Azure App Service, use AUTO guide to help user auto-instrument the app.
Manually instrument the app by creating the AppInsights resource and update the app's code.
Use one of the following options that fits the environment.
No matter which option you choose, recommend the user to create the App Insights resource in a meaningful resource group that makes managing resources easier. A good candidate will be the same resource group that contains the resources for the hosted app in Azure.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.
日本語の概要は準備中です。原文の説明を表示しています。
Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.
日本語の概要は準備中です。原文の説明を表示しています。
Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign planning or creative generation without performance data.
日本語の概要は準備中です。原文の説明を表示しています。
Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.
日本語の概要は準備中です。原文の説明を表示しています。