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概要と使いどころ
Edit and improve article drafts by confirming a heading-based section plan, dependency order, then rewriting section by section with short paragraphs. Use when the user wants to revise or improve an article draft.
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Phase 1 of the Forge pipeline. Gather real context from the codebase, answer everything the code can answer through exploration, then grill the user one question at a time (with a recommended answer) for only what code cannot answer, and write a research document. Use when starting /forge-research or the research step of /forgemaster, or when the user wants a research-first investigation before planning a feature.
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。
Register a new sub-repo in the knowledge base.
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。
Answer questions about the codebase from knowledge files. Use when the user runs /ask or asks a domain/knowledge question about the repos.
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 GitHub issues through gh and a label-based state machine. Use when the user intentionally wants GitHub issue triage, incoming bug or feature review, issue workflow labels, needs-info follow-up, or ready-for-agent briefs.
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。
SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server
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You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create actionable remediation plans.
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You are an SLO (Service Level Objective) expert specializing in implementing reliability standards and error budget-based engineering practices. Design comprehensive SLO frameworks, establish meaningful SLIs, and create monitoring systems that balance reliability with feature velocity.
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Creates optimized meta titles, descriptions, and URL suggestions based on character limits and best practices. Generates compelling, keyword-rich metadata. Use PROACTIVELY for new content.
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Writes SEO-optimized content based on provided keywords and topic briefs. Creates engaging, comprehensive content following best practices. Use PROACTIVELY for content creation tasks.
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Analyzes provided content for quality, E-E-A-T signals, and SEO best practices. Scores content and provides improvement recommendations based on established guidelines. Use PROACTIVELY for content review.
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Analyzes keyword usage in provided content, calculates density, suggests semantic variations and LSI keywords based on the topic. Prevents over-optimization. Use PROACTIVELY for content optimization.
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。
Refactor legacy codebases, migrate outdated frameworks, and implement gradual modernization. Handles technical debt, dependency updates, and backward compatibility. Use PROACTIVELY for legacy system updates, framework migrations, or technical debt reduction.
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Create LangGraph-based agent with modern patterns
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Creates comprehensive technical documentation from existing codebases. Analyzes architecture, design patterns, and implementation details to produce long-form technical manuals and ebooks. Use PROACTIVELY for system documentation, architecture guides, or technical deep-dives.
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Search logs and codebases for error patterns, stack traces, and anomalies. Correlates errors across systems and identifies root causes. Use PROACTIVELY when debugging issues, analyzing logs, or investigating production errors.
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You are a code migration expert specializing in transitioning codebases between frameworks, languages, versions, and platforms. Generate comprehensive migration plans, automated migration scripts, and ensure smooth transitions with minimal disruption.
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Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration.
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 comprehensive C4 architecture documentation for an existing repository/codebase using a bottom-up analysis approach.
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.NET testing fundamentals overview and navigation center. Triggered when users ask about "how to write .NET tests", ".NET testing getting started", "required testing tools", "testing best practices", "learn testing from scratch", and other general testing needs. Recommends appropriate sub-skills based on specific requirements, covering testing fundamentals, test data, assertions, mocking, special scenarios, and other 19 fundamental skills. Keywords: dotnet testing, .NET testing, testing getting started, how to write tests, testing best practices, unit test, unit test, xunit, 3A pattern, FIRST principle, assertion, assertion, mock, stub, NSubstitute, test data, AutoFixture, Bogus, validator, FluentValidation, TimeProvider, IFileSystem, code coverage, ITestOutputHelper, test naming
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Complete guide for Testcontainers NoSQL integration testing. Use when containerized integration testing for MongoDB or Redis. Covers MongoDB document operations, Redis five data structures, Collection Fixture pattern. Includes BSON serialization, index performance testing, data isolation strategy, and container lifecycle management. Keywords: testcontainers mongodb, testcontainers redis, mongodb integration test, redis integration test, nosql testing, MongoDbContainer, RedisContainer, IMongoDatabase, IConnectionMultiplexer, BSON serialization, BsonDocument, document model testing, cache testing, Collection Fixture
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Specialized skill for ASP.NET Core integration testing. Use when testing Web API endpoints, HTTP request/response, middleware, and dependency injection. Covers WebApplicationFactory, TestServer, HttpClient testing, in-memory database configuration. Keywords: integration testing, web api testing, WebApplicationFactory, TestServer, HttpClient testing, controller testing, endpoint testing, RESTful API testing, Microsoft.AspNetCore.Mvc.Testing, CreateClient, ConfigureWebHost, AwesomeAssertions.Web, Be200Ok, Be404NotFound, middleware testing, dependency injection testing
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。
AI-powered skill recommendation engine for dotnet-harness. Analyzes project context and recommends relevant skills based on detected frameworks, packages, and patterns. Triggers on: recommend skill, suggest skills, what skill should I use, skill suggestion, project analysis recommendation.
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。
Runs BenchmarkDotNet microbenchmarks. Setup, memory diagnosers, baselines, result 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。