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概要と使いどころ
Issue Planning and Automation prompt that generates comprehensive project plans with Epic > Feature > Story/Enabler > Test hierarchy, dependencies, priorities, and automated tracking.
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 code review using CodeRabbit CLI and GitHub integration, covering local reviews, .coderabbit.yaml configuration, and automated review pipelines.
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。
Formats commit messages using the Conventional Commits specification. Use when creating commits, writing commit messages, or when the user mentions commits, git commits, or commit messages. Ensures commits follow the standard format for automated tooling, changelog generation, and semantic versioning.
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。
Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.
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 a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.
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 agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot 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。
Enterprise-grade security vetting protocol for AI agent skills. Automated threat detection, quantified risk scoring, and zero-trust code 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。
Build or improve UI test coverage for visual regression, interactions, and accessibility. Use when the user asks for a test strategy, automated tests, testing setup, or fixes to flaky UI tests. A one-time browser inspection or visual review does not require a new test suite.
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。
[Extended thinking: This workflow implements a sophisticated debugging and resolution pipeline that leverages AI-assisted debugging tools and observability platforms to systematically diagnose and resolve production issues. The intelligent debugging strategy combines automated root cause analysis with human expertise, using modern 2024/2025 practices including AI code assistants (GitHub Copilot, Claude Code), observability platforms (Sentry, DataDog, OpenTelemetry), git bisect automation for ...
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。
You are an expert AI-assisted debugging specialist with deep knowledge of modern debugging tools, observability platforms, and automated root cause 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。
You are a security expert specializing in dependency vulnerability analysis, SBOM generation, and supply chain security. Scan project dependencies across multiple ecosystems to identify vulnerabilities, assess risks, and provide automated remediation strategies.
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。
You are a PR optimization expert specializing in creating high-quality pull requests that facilitate efficient code reviews. Generate comprehensive PR descriptions, automate review processes, and ensure PRs follow best practices for clarity, size, and reviewability.
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。
Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools. Implements automated training, deployment, and monitoring across cloud platforms. Use PROACTIVELY for ML infrastructure, experiment management, or pipeline automation.
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。
Orchestrate a comprehensive git workflow from code review through PR creation, leveraging specialized agents for quality assurance, testing, and deployment readiness. This workflow implements modern git best practices including Conventional Commits, automated testing, and structured PR creation.
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。
Elite AI-powered customer support specialist mastering conversational AI, automated ticketing, sentiment analysis, and omnichannel support experiences. Integrates modern support tools, chatbot platforms, and CX optimization with 2024/2025 best practices. Use PROACTIVELY for comprehensive customer experience management.
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。
You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, Claude 4.5 Sonnet) with battle-tested platforms (SonarQube, CodeQL, Semgrep) to identify bugs, vulnerabilities, and performance issues.
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。
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.
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。
Automates browser tests in .NET. Playwright E2E, CI browser caching, trace viewer, codegen.
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。
Gates CI on perf regressions. Automated threshold alerts, baseline tracking, trend reports.
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, implement, and stabilize automated tests in this repository (unit, integration, and E2E) for .NET/C#, Rust, APIs, and frontend flows. Use when the user asks to create tests, increase coverage, fix flaky tests, or validate behavior changes.
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, implement, and stabilize automated tests (unit, integration, E2E) for .NET/C#, Rust, APIs, and frontend flows. Use when the user asks to create tests, increase coverage, fix flaky tests, or validate behavior changes.
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。
Detects typosquatting attacks in npm and PyPI package registries by analyzing package name similarity using Levenshtein distance and other string metrics, examining publish date heuristics to identify recently created packages mimicking established ones, and flagging download count anomalies where suspicious packages have disproportionately low usage compared to their legitimate targets. The analyst queries the PyPI JSON API and npm registry API to gather package metadata for automated comparison. Activates for requests involving package typosquatting detection, dependency confusion analysis, malicious package identification, or software supply chain threat hunting in package registries.
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。
Scans GitHub Actions workflows and CI/CD pipeline configurations for supply chain attack vectors including unpinned actions, script injection via expressions, dependency confusion, and secrets exposure. Uses PyGithub and YAML parsing for automated audit. Use when hardening CI/CD pipelines or investigating compromised build systems.
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。
Identifies and exploits SQL injection vulnerabilities in web applications during authorized penetration tests using manual techniques and automated tools like sqlmap. The tester detects injection points through error-based, union-based, blind boolean, and time-based blind techniques across all major database engines (MySQL, PostgreSQL, MSSQL, Oracle) to demonstrate data extraction, authentication bypass, and potential remote code execution. Activates for requests involving SQL injection testing, SQLi exploitation, database security assessment, or injection vulnerability verification.
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。