「detect」の検索結果

Tactical DDD — aggregate design rules, entities, value objects, domain events, repositories, domain services, and anti-pattern detection

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。

Single Source of Truth detection — where truth lives in an nWave repo and how to avoid contradicting 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。

Canary skill for auto-injection detection

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 a PERSONAL brand needs AI avatar video at scale — three tool tiers, four workflows for single avatar, translation, batch, and hybrid, reference image intake, face, style, logo, and palette replacement, voice clone pairing, anti-detection, and a QA score, with disclosure-law variants for US FTC, EU AI Act, SEA, and LATAM, covering HeyGen and Synthesia. Trigger on 'AI avatar', 'HeyGen video', 'Synthesia', 'talking head AI video', 'translate my videos with AI', 'I cannot be on camera every day'. Not for — the words the avatar says, see `04-script-video-global`; audio-only voice clone and podcast, see `25-voice-clone-podcast-global`; a company product video edit, see `44-video-editor-brief-global`.

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 the user wants to monitor what is being said about the brand, competitors, and the category — channels and keywords to track, sentiment scoring, weekly and monthly listening reports, brand health metrics, early crisis detection, and content opportunities pulled from real conversations. Trigger on 'social listening', 'brand monitoring', 'sentiment analysis', 'what are people saying about us', 'track our mentions', 'monitor competitors online'. Also use when the user spotted a bad comment thread and wants to know if it is spreading. Not for — responding to a crisis already underway, see `66-crisis-playbook-global`; competitor strategy teardown, see `08-competitor-research-global`; auditing your own posts, see `39-content-audit-global`.

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。

Phase 0 of the prd-taskmaster pipeline. Resolves the active backend, initializes the project, configures the provider stack when the TaskMaster backend is active (DETECT-FIRST — never overwrite a working user config), and verifies the AI pipeline. Autonomous: zero user questions unless a hard block is hit. Declares the Setup phase complete so DISCOVER can follow.

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。

生成Windows批处理脚本，通过多维度检测（进程、全盘文件、注册表、已安装程序）来识别向日葵、TeamViewer等远程控制软件，并确保编码兼容性与执行稳定性。

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。

Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.

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。

Compose and Compose Multiplatform expert for UI development across Android, Desktop, iOS, and Web. Use whenever the user mentions Compose APIs (@Composable, remember, LaunchedEffect, NavHost, MaterialTheme, LazyColumn, Modifier, recomposition), Compose Multiplatform (commonMain, expect/actual, Res.*, ComposeUIViewController, UIKitView, ComposeViewport), Android TV (tv-material, D-pad, focus, Carousel), Material 3 motion, atomic design systems, design-to-code workflows, Paging 3, or navigation. Activates Review Mode on GitHub PR URLs and review phrases ("review this PR", "what's wrong with this"). Auto-detects Compose projects on session_start. Backed by actual androidx/androidx and JetBrains/compose-multiplatform-core source receipts. See "## When this skill applies" in SKILL.md for the full trigger surface.

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。

Probe for hardcoded secrets, injection surfaces, unguarded routes, business logic flaws, and platform-specific weaknesses across backend (Node, Go, Java, Python, Rust), frontend (React, Angular, Vue), and mobile (iOS, Android, Flutter) codebases. Use when performing security audits, vulnerability scans, secrets detection, or penetration 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。

Audit structural debt, logic leakage, and monolithic components across Web, Mobile, and Backend codebases. Use when reviewing architecture, assessing tech debt, detecting logic in wrong layers, or identifying God classes.

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。

Remove AI writing patterns from academic prose. Detects and fixes inflated symbolism, promotional language, superficial analyses, vague attributions, AI vocabulary, and formulaic structures. Supports English and Chinese. Triggers on "remove AI patterns", "humanize text", "anti-AI polish", "去除AI写作痕迹", "人性化处理".

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。

Detect version, preview changes, apply workflow upgrades

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。

Initialize project with auto state detection

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。

Use when the user asks which /phx-* command fits a task (review, plan, debug, test) or how two commands differ. Checks plans and git state, then recommends from the routing table. Not for bare /help, a tour, or ambiguous requests (intent-detection).

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。

Route ambiguous or mixed Phoenix/LiveView/Ecto requests; Use when user is unsure where to start/how to approach 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。

Use when the user asks which phx-* command fits a task (review, plan, debug, test) or how two commands differ. Checks plans and git state, then recommends from the routing table. Not for bare /help, a tour, or ambiguous requests (intent-detection).

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。

Detect N+1 query anti-patterns specifically — Repo calls inside Enum/for loops, missing preloads on associations. Use when N+1 is explicitly suspected, NOT for unrelated Ecto questions or wider database performance.

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 the user asks which /phx: command fits a task (review, plan, debug, test) or how two commands differ. Checks plans and git state, then recommends from the routing table. Not for bare /help, a tour, or ambiguous requests (intent-detection).

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。

Route ambiguous or mixed Phoenix/LiveView/Ecto requests before choosing a workflow. Use when user is unsure where to start/how to approach work, asks for the right workflow, or combines intents such as fixing and refactoring. NOT for a clear task.

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。

Detect N+1 query anti-patterns specifically — Repo calls inside Enum/for loops, missing preloads on associations. Use when N+1 is explicitly suspected, NOT for unrelated Ecto questions or wider database performance.

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 your Python environment and guides you through installing plugin dependencies. Use on first-time setup or when MCP server fails to start.

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。

This skill should be used when the user asks to "verify a fix", "reproduce failure", "diagnose issue", "check BEFORE/AFTER state", "VF task", "reality check", "check test quality", "mock-only tests", or needs guidance on verifying fixes by reproducing failures before and after implementation, or detecting mock-heavy test anti-patterns.

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。