Updates Azure Verified Module (AVM) references in a Bicep file to their latest versions, applying only non-breaking changes and reporting the result as a table. Use when Bicep templates pin outdated AVM versions or before an infrastructure release.
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 when writing, editing, or reviewing code, READMEs, docs, commits, changelogs, or any repo content. Pre-2020 human style — terse, opinionated, restrained, with project voice. Blocks the LLM tics (emoji headers, "leverage", "robust", "seamless", "delve", defensive bloat, type-hint overkill, marketing prose, "Whether you're X or Y", verbose error messages) catalogued from cpython, requests, flask, git, ripgrep, express, kubernetes, serde, and the Go stdlib. Triggers on "anti-ai", "human-style", "no slop", "write it like a human", or any time code/docs should look hand-written.
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。
Enforce output quality, evidence verification, and quality gates across security audits. Use this skill when you perform SAST, SCA, threat modeling, or security code reviews. Use this skill to verify code locations and taint traces for all findings. Use this skill to prevent the suppression of valid security findings. Use this skill to evaluate reports against quality thresholds (score ≥ 8/10) before delivery.
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。
Performs security-focused differential review of code changes. Adapts analysis depth to codebase size, uses git blame for context, calculates blast radius by counting callers, checks test coverage of modified code, and generates a markdown report. Use when reviewing a PR, commit, or diff for security vulnerabilities, checking whether a change re-introduces a previously fixed bug, asking what else a change could break, or finding which modified code has no test covering it.
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 when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
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。
Reviews and refactors code according to the project's own instruction and guideline files, keeping behavior intact. Use when the user asks for a cleanup pass that must follow repository conventions (for example .github/instructions) rather than generic 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。
Generate personalized status briefings on demand. Pulls from your configured data sources (GitHub, email, Teams, Slack, and more), synthesizes across them, and drafts updates in your own communication style for any audience you define
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 when designing new API endpoints, defining module boundaries or contracts between teams, creating component prop interfaces, or changing an existing public interface. Covers naming, versioning, error shapes, and designing surfaces that are hard to misuse.
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 when setting up a project's CI pipeline, adding or changing automated checks, configuring deployment pipelines, or debugging CI failures. Covers quality gates, pipeline stages, and what to verify automatically on every change.
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 when working code feels heavier than it needs to be — deeply nested logic, long functions, unclear names, duplication after a merge, or a review that flagged complexity. Reduces complexity while preserving behavior exactly. Not for code you do not yet understand, or code you are about to rewrite.
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 when building or modifying user-facing interfaces: new components and pages, responsive layouts, interactivity and state management, or fixing visual and UX issues. Covers component architecture, styling, accessibility, and state boundaries.
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。
Reverse-engineers and debugs macOS and iOS binaries with Hopper Disassembler and LLDB: ObjC/Swift symbols, dyld loading, framework internals, and crash investigation from disassembly. Use when private API behavior or a runtime crash needs to be understood at the binary level.
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 when refining a vague idea through divergent expansion, convergent focus, and assumption stress-testing before planning or implementation.
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。
Delivers changes incrementally. Use when implementing any feature or change that touches more than one file. Use when you're about to write a large amount of code at once, or when a task feels too big to land in one step.
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。
Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invokes ("interview me", "grill me", "are we sure?", "stress-test my thinking"), or when you catch yourself silently filling in ambiguous requirements before any plan, spec, or code exists.
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。
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
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 when writing, reviewing, or refactoring production code where reliability, portability, maintainability, explicit contracts, resource safety, and cross-language coding standards matter across Python, TS/JS, C, C++, Rust, or Go.
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。
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available 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。
Use when building anything that accepts user input, implementing authentication or authorization, storing or transmitting sensitive data, integrating external APIs, or adding file uploads, webhooks, or callbacks. Covers input validation, secrets, authz checks, and PII and payment handling.
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 given method `${input:methodName}` to reduce its cognitive complexity to `${input:complexityThreshold}` or below, by extracting helper methods. Use when a method exceeds a cognitive-complexity threshold flagged by a linter or review.
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。
Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.
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。
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production auth, security-sensitive logic, a high-stakes migration, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
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。
Profiles macOS and iOS apps with Instruments and xctrace: choosing templates such as Time Profiler, launching binaries with arguments, recording traces, and exporting results. Use when a Mac or iOS app needs CPU, memory, or responsiveness profiling.
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。
Profiles native macOS and iOS apps from the command line only: xctrace recording, Time Profiler samples, hotspot ranking, and symbolication with atos and vmmap. Use for headless or SSH-based performance analysis without opening the Instruments GUI.
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。