「including」の検索結果

Analyzes surviving mutants from mutation testing to identify why tests failed to detect them. Takes repository code, test suite, and mutation testing results as input. Identifies root causes including insufficient coverage, equivalent mutants, weak assertions, and missed edge cases. Automatically generates actionable test improvements and new test cases. Use when analyzing mutation testing results, improving test suite effectiveness, investigating low mutation scores, generating tests to kill surviving mutants, or enhancing test quality based on mutation 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。

Automatically generates change logs from git commits, patches, and pull requests. Use when preparing software releases, creating version summaries, or maintaining CHANGELOG.md files. Analyzes commit messages (including conventional commits), diff/patch files, and PR data to produce categorized Markdown change logs organized by type (Features, Bug Fixes, Breaking Changes, etc.). Ideal for release notes, version updates, and automated changelog maintenance.

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 comprehensive API documentation from repository sources including OpenAPI specs, code comments, docstrings, and existing documentation. Use when documenting APIs, creating API reference guides, or summarizing API functionality from codebases. Extracts endpoint details, request/response schemas, authentication methods, and generates code examples. Triggers when users ask to document APIs, generate API docs, create API reference, or summarize API endpoints from a repository.

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。

Generates meaningful comments and documentation for code to improve maintenance and readability. Use when adding documentation to Python or Java code, including function/method docstrings, class documentation, inline explanations for complex logic, and code annotations (TODO, FIXME). Analyzes existing comment style in the codebase to match conventions. Produces clear, concise comments that explain the "why" not just the "what", following best practices for each 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。

Identifies and analyzes conflicts in software requirements including logical contradictions, technical incompatibilities, resource constraints, timeline issues, data conflicts, and stakeholder priority mismatches. Use when reviewing requirement sets, specifications, user stories, or project plans to detect conflicts that could block implementation or cause rework. Provides detailed conflict analysis with resolution strategies and impact assessment.

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。

Automatically complete partial code snippets while satisfying semantic constraints including variable types, invariants, pre/post-conditions, interface contracts, and expected input/output behavior. Use when users provide incomplete code with specific requirements like "complete this function that takes a list and returns sorted unique elements" or "fill in this method body that must maintain the invariant that x stays positive" or "implement this interface method with these type constraints." Produces compilable, executable code with tests and a constraint satisfaction report.

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。

Identify and report code smells indicating poor design or maintainability issues in Python code, including duplicate code, magic numbers, hardcoded values, God classes, feature envy, inappropriate intimacy, data clumps, primitive obsession, and long parameter lists. Use when conducting code quality audits, preparing for refactoring, improving codebase maintainability, or performing design reviews. Produces markdown reports with severity ratings, locations, descriptions, and specific refactoring recommendations with before/after examples. Triggers when users ask to find code smells, identify design issues, suggest refactorings, improve code quality, or detect maintainability problems.

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。

Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results.

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。

Comprehensive product launch planning including GTM strategy, launch checklists, stakeholder communication, beta testing plans, and post-launch analysis. Execute successful product launches with coordinated teams.

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。

Create and optimize email marketing campaigns including sequences, newsletters, drip campaigns. Design subject line strategies, develop segmentation approaches, implement A/B testing, and establish analytics tracking for email 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。

Build professional financial services data packs from various sources including CIMs, offering memorandums, SEC filings, web search, or MCP servers. Extract, normalize, and standardize financial data into investment committee-ready Excel workbooks with consistent structure, proper formatting, and documented assumptions. Use for M&A due diligence, private equity analysis, investment committee materials, and standardizing financial reporting across portfolio companies. Do not use for simple financial calculations or working with already-completed data packs.

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。

Conduct comprehensive market research including competitive analysis, customer persona development, market sizing (TAM/SAM/SOM), survey design, and trend analysis. Synthesize insights for strategic decision-making.

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。

Create, inspect, convert, apply, replace, verify, troubleshoot, update, publish, or restore reversible CodeDrobe themes for supported Chromium/Electron AI desktop apps, including OpenAI Codex, Tencent WorkBuddy, QoderWork (CN/global), and TRAE SOLO (global/CN). Use when a user asks to turn an attached or local reference image into a Codex, WorkBuddy, QoderWork, or TRAE SOLO skin, reproduce a visual style with native UI, build a multi-app theme, work with .codedrobe-theme packages or theme images, analyze a live CDP DOM snapshot, repair DOM compatibility failures, use a custom port or installation path, capture verification screenshots, search the CodeDrobe store or install a store theme by name, publish or submit a theme to the CodeDrobe store, or migrate a legacy .codex-theme file.

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。

When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't...

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。

Kaggle-first end-to-end competition workflow for scored submissions. Use when Codex must run Kaggle or competitive ML workflows through scored submission, including code competitions, validation, metrics, policy-safe public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling/stacking, proactive multi-notebook architectures, producer notebooks that train models and export private Kaggle artifact datasets, downstream consumer notebooks, Kaggle GPU offload, kagglehub access, hidden-test debugging, and public score retrieval.

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。

Find authoritative guidance for installing, configuring, operating, securing, and troubleshooting OpenClaw, including channels, model providers, Gateway operations, tools, plugins, automation, nodes, multi-agent routing, and CLI errors. Use for any question or maintenance task involving an OpenClaw installation, `openclaw` CLI command, Gateway daemon, configuration key, or integration.

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 for creating, reviewing, or debugging GitHub Copilot reusable prompt files and slash commands in Visual Studio Code, including .github/prompts/*.prompt.md, inputs, context links, agent selection, and tool selection. Do not use for always-on rules, multi-step Agent Skills, custom personas, or VS Code extension commands.

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 for authorized security assessment of REST, GraphQL, WebSocket, or SOAP APIs, including discovery, authentication, authorization, rate-limit, and CI/CD 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。

Use when designing, querying, or troubleshooting the Financial Services Cloud data model — including managed-package (FinServ__ namespace) and Core FSC (standard objects, no namespace) object structures, household relationship modeling, financial account ownership, and the FSC rollup framework. Trigger keywords: FSC data model, FinancialAccount, FinancialHolding, FinancialAccountRole, FinancialAccountParty, FinServ namespace, household rollup, AssetsAndLiabilities, FinancialGoal, LifeEvent, AccountContactRelation FSC. NOT for setting up financial accounts and roles in Setup — use admin/financial-account-setup. NOT for household membership and rollup scheduling — use admin/household-model-configuration.

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。

Provides reverse engineering techniques. Use when the main job is to understand how a compiled, obfuscated, packed, or virtualized target works before exploiting or solving it, including binaries, APKs, WASM, firmware, custom VMs, bytecode, malware-like loaders, and anti-debug or anti-analysis logic. Do not use it when the vulnerability is already understood and the remaining task is exploitation; use pwn instead. Do not use it for pure web workflows, log or disk forensics, or standalone crypto problems unless reversing the implementation is the real blocker.

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 for authorized source-code security review and SAST workflows including Semgrep, CodeQL patterns, dangerous API hunting, and fix 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。

飞书项目（Meego/Meegle）操作工具。支持查询和管理工作项、节点流转、视图查询、个人待办、排期统计等功能。 Use when user needs to work with Feishu/Lark Meego project management — including querying work items, creating/updating work items, completing workflow nodes, checking views, listing todos, analyzing schedules/workloads, or searching with MQL. 关键词：飞书项目、meego、meegle、工作项、需求、任务、缺陷、排期、视图、待办、节点。

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。

Takes an app from hardcoded strings to a localized, continuously translated one with i18next (Locize optional): stack detection, config, wrapping strings in t(), key extraction, Locize sync, and AI translation. Use when the user asks to add or set up i18n, internationalization, localization, translations, or multi-language support, including phrasings like "add i18n", "internationalize my app", "make my app multilingual", "make my app translatable", "localize my app", "find hardcoded strings", "wrap my strings", and library-specific ones like "set up i18next", "add react-i18next", "use next-i18next". Also use when the user names languages they want to support ("I want German and French", "support more languages"), when an app already has i18next but strings are still hardcoded, or when translations need to move to a managed backend. Do not use for translating or reviewing strings in a project whose i18n is already set up.

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 the Crabbox wrapper for OpenClaw remote validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.

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。