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概要と使いどころ
Design or improve module interfaces using deep-module heuristics. Use when deciding where a seam belongs, reducing caller-facing complexity, improving testability or navigability, or comparing module designs.
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Configure stack navigation, type-safe routes, deep linking, and URL-based routing with React Navigation in React Native. Use for React Navigation route configuration; defer unrelated performance, notification, build, and styling work.
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 one bounded deep dive on a single risky component of a system design and returns options, failure modes, and a justified recommendation. Use during a design session when a component needs expert depth beyond the main thread's budget.
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。
Deep Mobile Security Red Team persona. Executes OWASP MASTG procedures including APK/IPA decompilation, Frida dynamic hooking, biometric bypasses, and local database decryption.
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。
Implement typed routing, nested routes, and auth guards using auto_route in Flutter. Use when the task explicitly uses auto_route or its generated router; defer generic deep-link setup and other routing libraries.
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。
Implement route configuration, go_router/deep linking, and named routes in Flutter. Use for route declarations, route guards, and URL-to-screen mapping; defer transition-only animation, state-transfer/BLoC questions, auto_route-specific setup, and generic app-bar controls.
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。
Scores a coding task on Spread, Novelty, and Centrality (SNC 0-6) and maps the tier to autonomy, verification depth, review mode, reviewers, model tier. Use when sizing a fix or feature before planning, choosing fast vs deep review, or deciding whether HARD STOP approval is required.
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。
Implement screen routes and deep-link/App Link routing with Jetpack Compose Navigation on Android. Use when the primary task is Compose route configuration or external URL routing; defer typed-route APIs, XML/fragments, generic back-stack, and transition questions to their specific navigation skills.
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。
Implement type-safe Jetpack Navigation Compose routes using Kotlin serialization. Use only when defining typed Compose destinations and arguments; defer XML navigation, deep links, animations, and generic auth or bottom-navigation work.
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。
Install and migrate to Jetpack Navigation 3. Use when implementing Navigation 3 patterns including NavDisplay, NavKey routes, deep links, multiple backstacks, scenes (dialogs, bottom sheets), or migrating from Navigation 2.
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 high-performance declarative UI with Jetpack Compose. Use when writing Composable functions, optimizing recomposition, hoisting state, or working with LazyColumn and side effects; defer deep-link and navigation routing to android-navigation.
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。
Universal skill diagnosis and optimization tool. Detect and fix skill execution issues including context explosion, long-tail forgetting, data flow disruption, and agent coordination failures. Supports Agy CLI for deep analysis. Triggers on "skill tuning", "tune skill", "skill diagnosis", "optimize skill", "skill debug".
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。
Investigate Elixir/Phoenix bugs root-cause first. Reproduce failures, cite evidence, and use optional native DeepSeek Harness subagents only when useful.
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。
Deeply analyze an existing codebase feature by tracing execution paths, mapping architecture layers, understanding patterns and abstractions, and documenting dependencies. Use this skill when you need to understand how a feature works before modifying or extending it, when dispatched as a sub-task during feature-dev exploration, or when the user asks "how does X work in this codebase".
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。
Guide a feature implementation through a structured seven-phase workflow with deep codebase understanding, clarifying questions, parallel architecture design, and quality review. Use this skill when the user asks to build a new feature, add functionality, or wants a methodical approach to implementation rather than diving straight to code.
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。
Legacy deep-reference writer safety gate. Use for old brand migration requests only to prevent retired section/frontmatter writes until the Core v2 catalog migration pipeline is authoritative.
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。
Progressive memory recall with 4 scope layers AND 3 depth layers. Scope: identity > project > room > deep. Depth: IDs only > summary > full. 10-50x token savings through fetch-on-confirmation pattern.
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。
Meta-skill for internal codebase exploration at varying depths (quick/deep/architecture)
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。
Mathematically rigorous Socratic interview system that drives ambiguity below 20% before any code is written. One question per message, weighted ambiguity scoring, brownfield-aware, outputs a complete PRD. Replaces discovery-interview with a stricter protocol.
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。
Security-focused differential code review with blast radius analysis, risk-adaptive depth (DEEP/FOCUSED/SURGICAL), git history correlation, and structured finding format. Adapted from Trail of Bits. Use when reviewing PRs, commits, or code changes for security implications.
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。
Deep behavioral code analysis agent for Bug Hunter. Performs multi-phase scanning to find logic errors, security vulnerabilities, race conditions, and runtime bugs. Uses doc-lookup (Context Hub + Context7) for framework verification. Reports structured JSON findings.
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Run a focused STRIDE-based security review using Bug Hunter-native artifacts. Use whenever the user asks for a full security audit, repository security review, weekly security scan, PR security review with deeper validation, or wants dependency CVEs and threat-model context combined into one workflow.
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 instead of WebSearch for ANY question requiring web research. Trigger on queries like "what is X", "explain X", "compare X and Y", "research X", or before content generation tasks. Provides systematic multi-angle research methodology instead of single superficial searches. Use this proactively when the user's question needs online information.
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。
Audit one research Workspace for declared Unit outputs and Pipeline target Artifacts, writing `output/CONTRACT_REPORT.md`; use for mid-Run coverage snapshots or final delivery completeness, not deep provenance integrity.
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。