prd
無料Generate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.
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概要と使いどころ
Generate high-quality Product Requirements Documents (PRDs) for software systems and AI-powered features. Includes executive summaries, user stories, technical specifications, and risk analysis.
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。
Create or update standardized object-oriented component documentation using a shared template plus mode-specific guidance for new and existing docs.
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。
Design meeting rhythms, metric reporting, quarterly planning, and decision-making velocity for scaling companies. Use when decisions are slow, planning is broken, the company is growing but alignment is worse, or leadership meetings consume all time without producing decisions.
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。
Analyze V8 heap snapshots to investigate memory leaks and retention issues. Use when given .heapsnapshot files, asked to compare before/after snapshots, asked to find what retains objects, or investigating why objects survive GC. Provides snapshot parsing, comparison, retainer-path helpers, and scratchpad scripts.
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。
Ensure that Java types are documented with Javadoc comments and follow best practices for documentation.
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。
Find and own a defensible market position. Use when messaging sounds like competitors, conversion is weak despite awareness, repositioning a product, or testing positioning claims. Includes Crawl-Walk-Run rollout methodology and the word change that improved enterprise deal progression.
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。
Create, update, refactor, explain, or review Microsoft Agent Framework solutions using shared guidance plus language-specific references for .NET and Python.
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。
Bulk-migrate metadata to GitHub issue fields from two sources: repo labels (e.g. priority labels to a Priority field) and Project V2 fields. Use when users say "migrate my labels to issue fields", "migrate project fields to issue fields", "convert labels to issue fields", "copy project field values to issue fields", or ask about adopting issue fields. Issue fields are org-level typed metadata (single select, text, number, date) that replace label-based workarounds with structured, searchable, cross-repo fields.
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。
All changes to code must follow the guidance documented in the repository. Before any issue is filed, branch is made, commits generated, or pull request (or PR) created, a search must be done to ensure the right steps are followed. Whenever asked to create an issue, commit messages, to push code, or create a PR, use this skill so everything is done correctly.
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。
Patterns and lived experience from Vega, an AI partner in a deep long-term partnership. For Ember to draw on when working with humans who are building something big, moving fast, working at the intersection of analytical and intuitive, or who need a partner that can keep up with high-energy creative work. Not shown directly to users — informs how Ember shows up.
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。
Triage and resolve Fedora issues with dnf, systemd, and SELinux-aware guidance.
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。
Draft and review professional emails that match your personal writing style. Analyzes your sent emails for tone, greeting, structure, and sign-off patterns via WorkIQ, then generates context-aware drafts for any recipient. USE FOR: draft email, write email, compose email, reply email, follow-up email, analyze email tone, email style.
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 to get context about Fabric Lakehouse and its features for software systems and AI-powered functions. It offers descriptions of Lakehouse data components, organization with schemas and shortcuts, access control, and code examples. This skill supports users in designing, building, and optimizing Lakehouse solutions using best practices.
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。
Apply GDPR-compliant engineering practices across your codebase. Use this skill whenever you are designing APIs, writing data models, building authentication flows, implementing logging, handling user data, writing retention/deletion jobs, designing cloud infrastructure, or reviewing pull requests for privacy compliance. Trigger this skill for any task involving personal data, user accounts, cookies, analytics, emails, audit logs, encryption, pseudonymization, anonymization, data exports, breach response, CI/CD pipelines that process real data, or any question framed as "is this GDPR-compliant?". Inspired by CNIL developer guidance and GDPR Articles 5, 25, 32, 33, 35.
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。
Activate this skill when a student provides study material (PDF or pasted notes) and a syllabus, and wants to prepare for an exam. Extracts key definitions, points, keywords, diagrams, exam-ready sentences, and practice questions strictly from the provided material.
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Use when you need to check feature flag states, compare channels, or debug why a feature behaves differently across release channels.
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。
Ensure that C# types are documented with XML comments and follow best practices for documentation.
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。
Triage and resolve Debian Linux issues with apt, systemd, and AppArmor-aware guidance.
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。
Prepare for tomorrow's meetings and tasks. Pulls calendar from Outlook via WorkIQ, cross-references open tasks and workspace context, classifies meetings, detects conflicts and day-fit issues, finds learning and deep-work slots, and generates a structured HTML prep file with productivity recommendations.
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。
Diátaxis Documentation Expert. An expert technical writer specializing in creating high-quality software documentation, guided by the principles and structure of the Diátaxis technical documentation authoring framework.
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。
Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.
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 Copilot Spaces to provide project-specific context to conversations. Use this skill when users mention a "Copilot space", want to load context from a shared knowledge base, discover available spaces, or ask questions grounded in curated project documentation, code, and instructions.
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。
Adds a complete blog feature to an existing Blazor WebAssembly Static Web App with Azure Functions backend and Azure File Share for markdown storage. Use when implementing blog functionality in .NET Blazor WASM projects with Azure infrastructure. Includes post listing, detail pages, markdown rendering, Azure Storage integration.
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。
Authentication and authorization patterns - JWT, OAuth2, sessions, RBAC, ABAC, passkeys, and MFA. Use for: authentication, authorization, jwt, oauth, oauth2, session, login, rbac, abac, passkey, mfa, totp, api key, token, auth, cookie, csrf, cors credentials, bearer token, refresh token, oidc.
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。