「common」の検索結果

Use ONLY when calling the `browser_execute` tool or driving a real browser via the Chrome DevTools Protocol. Required reading before the first `browser_execute` call in a session. Covers the three connection methods (local Chrome with remote debugging, isolated debug-port profile, Browser Use cloud), the in-process `session` / `console` snippet model, attaching to a page target, common CDP commands, the per-project `.bcode/agent-workspace/` for reusable scripts, and screenshot auto-attachment.

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。

Smartlead API endpoint reference and patterns. Use for any Smartlead campaign, lead, email account, analytics, or inbox operation. Covers auth, rate limiting, and all commonly used endpoints.

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。

Common design patterns with Java examples (Factory, Builder, Strategy, Observer, Decorator, etc.). Use when user asks "implement pattern", "use factory", "strategy pattern", or when designing extensible components.

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。

JPA/Hibernate patterns and common pitfalls (N+1, lazy loading, transactions, queries). Use when user has JPA performance issues, LazyInitializationException, or asks about entity relationships and fetching 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。

Analyzes your Claude Code conversation history to identify patterns, common mistakes, and opportunities for workflow improvement. Use when user wants to understand usage patterns, optimize workflow, identify automation opportunities, or check if they're following 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。

覆盖批量任务完整生命周期：参数叉乘创建、猴子补丁钩子追踪队列提交与执行、状态聚合状态机、队列中断取消、文件清理删除。 导航时机：理解批量任务从创建到完成的全流程、调试端到端任务生命周期问题、修改任务状态转换、排查任务卡住、新增生命周期阶段或状态。 排除：结果处理与输出媒体处理（见 ../result-processing/）、资源上传管理、前端UI逻辑。 关键词: 批量任务生命周期, createBatchTask, cancelTask, deleteTask, post_prompt, task_start, task_done, BatchToolsHandler, SubTaskStatus, CommonTaskStatus, prompt_queue, 猴子补丁, 参数叉乘, 状态聚合, 队列执行, 文件清理, SQLite WAL。

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。

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production 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。

4-step system design framework with back-of-envelope estimation, scaling ladder, and common pitfalls

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。

Shared artifact registry, common artifact patterns, and integration validation. Load when tracking data that flows across journey steps or validating horizontal coherence.

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。

JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes

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。

Pointer to the upstream skill for behavioural guidelines that reduce common LLM coding mistakes, installed from upstream.

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。

Secure Go backend services against common vulnerabilities. Use when implementing input validation, crypto, or SQL injection prevention in 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。

Standardize SRS and FRS specifications for technical behavior, interfaces, data contracts, quality constraints, and verification mapping. Use when writing SRS, functional specification, system behavior requirements, API/data contracts, or non-functional thresholds.

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。

Standardizes visual audits, responsive design, and behavioral testing for web apps. Use to verify a web UI fix or cross-browser behavior; defer backend API refactors, Playwright installation/tooling setup, and Appium/mobile 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。

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。

Standardize dynamic application security testing for backend APIs, frontend web apps, and mobile clients. Covers ZAP, Nuclei, Nikto, sqlmap, ffuf, browser automation, mobile proxy interception, and AI-driven curl probes. Use when advising on or running dynamic security scans on local/staging environments.

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 universal standards for high-performance development. Use when profiling bottlenecks, reducing latency, fixing memory leaks, improving throughput, or optimizing algorithm complexity in any language.

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。

Define the delivery metrics contract for agent-assisted SDLC — DORA four plus per-stage indicators derived from artifact and git history, and the control bands that turn metric drift into a routed intake. Use when reporting cycle time, plan adherence, or defining response thresholds.

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。

Standardizes mobile UI audits, performance/scroll checks, RTL verification, and state-specific testing on iOS/Android.

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。

Infer the requesting operator's technical fluency from message content (never ask directly) and adapt register — business, hybrid, or technical — across SDLC workflow output. Use when starting sdlc, brainstorm-feature, plan-feature, verify-work, publish-notes, or session-report, or whenever a request's phrasing signals a non-technical or cross-stack operator.

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 distinctive, production-grade frontend UI with bold aesthetic choices. Use when building web components, pages, interfaces, dashboards, or applications in any framework (React, Next.js, Angular, Vue, HTML/CSS).

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。

Standardizes the creation and evaluation of high-density Agent Skills (Claude, Cursor, Windsurf). Ensures skills achieve high Activation (specificity/completeness) and Implementation (conciseness/actionability) scores. Use when: writing or auditing SKILL.md, improving trigger accuracy, or refactoring skills to reduce redundancy and maximize token ROI.

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。