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概要と使いどころ
Track validated Codex Security findings in Linear, Jira, GitHub issues, or draft GitHub security advisories. Supports issue batches, duplicate checks, and reviewed writes. Do not use for scans or fixes.
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。
Evidence-first pull request judge that reviews a PR and posts one consolidated GitHub review with inline comments via the gh CLI. Runs the repo's own deterministic checks first, researches current official docs before any claim about external libraries or APIs, then reviews correctness, security, structural quality (code judo, spaghetti growth, file-size limits), and AI slop including useless code comments. Every finding must carry evidence, every comment passes a deterministic noise gate before posting, and the verdict (APPROVE, COMMENT, REQUEST_CHANGES) is weighed by findings. Use when asked to review a PR, judge this PR, review this branch or diff before merge, run the-judge, "revise esse PR", "faca o code review", or "julgue esse PR". Do NOT use for reviewing prose or documents, fixing CI failures, resolving merge conflicts, writing the fix itself, or responding to review comments (use gh-address-comments).
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 a sequenced monolith-to-modular pipeline that sizes and inventories components, finds shared domain duplication, addresses flattening and hierarchy issues, analyzes coupling, then groups components into candidate domain-aligned units, with optional embedded DDD strategic analysis for bounded contexts. Use when asking how to split a monolith, size components before extraction, find duplicated domain logic, clean up module hierarchy, measure coupling between modules, or group components into services. Do NOT use for phased extraction roadmaps or prioritization without the prior analysis steps (use decomposition-planning-roadmap after this pipeline), end-to-end legacy migration strategy writeups (use legacy-migration-planner), pure infrastructure capacity sizing, or when you only need DDD without the structural pipeline (install domain-analysis standalone).
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 misplaced classes and fixes component hierarchy problems — finds code that should belong inside a component but sits at the root level. Use when asking "clean up component structure", "find orphaned classes", "fix module hierarchy", "flatten nested components", or analyzing why namespaces have misplaced code. Do NOT use for dependency analysis (use coupling-analysis) or domain grouping (use domain-identification-grouping).
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。
Finds duplicate business logic spread across multiple components and suggests consolidation. Use when asking "where is this logic duplicated?", "find common code between services", "what can be consolidated?", "detect shared domain logic", or analyzing component overlap before refactoring. Do NOT use for code-level duplication detection (use linters) or dependency analysis (use coupling-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。
Find businesses, leads, emails, reviews, ratings, and contact details from Google Maps. Use for requests such as "find dentists in Berlin", "scrape Google Maps", "get local business leads", or "collect Google Maps reviews". Runs the open-source scraper locally with Docker and guides nontechnical users through setup, monitoring, and 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。
This skill helps users automatically extract structured channel data from YouTube search results via BrowserAct API. Agent should proactively apply this skill when users express needs like finding YouTube channels about specific topics, collecting data on YouTube content creators, tracking YouTube influencers in specific industries, getting YouTube channel information for competitor analysis, searching for YouTube channels related to keywords, monitoring YouTube channel updates for specific keywords, finding YouTube channels that recently published videos, extracting YouTube channel subscriber counts, discovering YouTube vloggers in specific niches, building a YouTube channel database for market research, batch extracting YouTube channel links and descriptions, or monitoring competitor channel growth.
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。
Searches Threads posts by keyword or hashtag and returns matching posts with engagement metrics, extracted from SSR-embedded JSON. Use when user asks to search Threads posts, find Threads content by topic, scrape Threads search results, collect Threads posts about a keyword, monitor Threads hashtag activity, pull Threads posts mentioning a term, gather Threads content by hashtag, search for posts on Threads, extract Threads search feed, get trending posts on Threads, find Threads discussions about a subject, or fetch recent or top Threads posts by keyword.
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。
YouTube channel business email and contact extractor: accepts a channel id (UCxxx), handle (@name), or URL; navigates the channel About view; extracts the business email from the description text plus full channel metadata (name, id, country, subscriber count, view count, video count, joined date, external links classified as social/aggregator/personal). When the description has no email, follows non-social outbound links (personal site, business site, link aggregator) and scans those pages for an email so creators who place their inquiry email on their own site are still covered. Use when user mentions youtube channel email, youtube business email, youtube creator email, youtube contact email, youtube channel contact, youtube channel scraper email, youtube email finder, youtube influencer email, youtube outreach, youtube sponsorship contact, youtube partnership email, scrape email from youtube, get email from youtube channel, find youtube creator contact, extract youtube channel emails in bulk, youtube channel inquiry email, business inquiries youtube, brand deal email youtube, lead generation youtube creators, youtube creator outreach list, youtube channel about email, ytInitialData about, youtube channel id to email, youtube handle to email, youtube channel url to email, youtube about page scraper, channel about page email, youtube channel metadata, youtube channel social links, youtube channel external links, youtube channel description email, follow channel website for email, scrape creator personal website from youtube. Also applies to building creator/KOL contact databases for influencer marketing, agency lead lists, sponsorship prospecting, brand-creator collaboration sourcing, and enriching existing YouTube channel lists with contact info.
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 is designed to help users automatically extract business data from Google Maps search results. The Agent should proactively apply this skill when the user makes the following requests searching for coffee shops in a specific city, finding dentists or medical clinics nearby, tracking competitors' locations in a certain area, extracting business leads from Google Maps lists, gathering restaurant data for market research, finding hotels or accommodation options in a region, locating specific services like coworking spaces or gyms, monitoring new business openings in a neighborhood, collecting contact information and addresses for sales prospecting, analyzing price ranges and cuisines of local eateries, getting ratings and review counts for a list of businesses, exporting local business data into a CRM or database.
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 helps users discover key contacts across industries, roles, and social platforms via the BrowserAct API. Agent should proactively apply this skill when users express needs like finding public profiles for founders or CEOs, discovering key decision-makers in a specific industry, extracting contact details for lead generation, searching for growth leaders on LinkedIn or Facebook, gathering professional networking profiles, retrieving URLs and names of industry leaders, finding marketing managers in a specific field, conducting competitive analysis by identifying key personnel, sourcing talent acquisition targets across platforms, or compiling a list of target roles on specific social sites.
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 helps users automatically scrape business data from Google Maps using the BrowserAct Google Maps API. Agent should proactively trigger this skill for needs like finding restaurants in a specific city, extracting contact info of dental clinics, researching local competitors, collecting addresses of coffee shops, generating lead lists for specific industries, monitoring business ratings and reviews, getting opening hours of local services, finding specialized stores (e.g., Turkish-style restaurants), analyzing business categories in a region, extracting website links from local businesses, gathering phone numbers for sales outreach, mapping out service providers in a specific country.
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 is designed to help users automatically extract product data from Amazon search results. The Agent should proactively apply this skill when users request searching for products related to keywords, finding best-selling items from specific brands, monitoring product prices and availability on Amazon, extracting product listings for market research, collecting product ratings and review counts for competitive analysis, finding specific products with a maximum count, searching Amazon in different languages for localized results, tracking monthly sales estimates for brand products, gathering product URLs and titles for a product catalog, scanning Amazon for Best Seller tags in a specific category, monitoring shipping and delivery information for brand items, building a structured dataset of Amazon search 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。
This skill helps users extract structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications. Use this skill when users want to search for products on Amazon, find the best selling brand products, track price changes for items, get a list of categories with high ratings, compare different brand products on Amazon, extract Amazon product data for market research, look for products in a specific language or marketplace, analyze competitor pricing for keywords, find featured products for search terms, get technical specifications like material or color for product lists.
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 helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market 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。
This skill helps users automatically extract official website and social media profiles. Agent should proactively apply this skill when users express needs like search for official website and social media contacts of a company, find YouTube and LinkedIn profiles by company name, extract social media links from a specific website URL, discover a company's X and Facebook presence, gather business contact details using their brand name, retrieve TikTok and Instagram links from a target website, track competitor social media strategy, extract multi-platform social links for lead generation, find official contact channels of local businesses, collect canonical profile URLs for outreach campaigns, or build a contact database from Yellow Pages leads.
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。
Helps find, inspect, and compare (at a high level) .NET project templates. Resolves natural-language project descriptions to ranked template matches with pre-filled parameters. USE FOR: finding the right dotnet new template for a task, inspecting a template's parameters and constraints, understanding what a template produces before creating a project, resolving intent like "web API with auth" to concrete template + parameters. DO NOT USE FOR: actually creating projects (use template-instantiation), authoring custom templates (use template-authoring), producing a detailed side-by-side comparison (use template-comparison), choosing cross-parameter defaults during creation (use template-smart-defaults), MSBuild or build issues (use dotnet-msbuild plugin), NuGet package management unrelated to template packages.
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。
MANDATORY for static source-to-test pairing: find or list source files/modules without corresponding tests, or suggest test locations from repository structure. Invoke even for a tiny package; do not substitute manual globbing. Uses Roslyn for C#/.NET and tree-sitter for Python, TS/JS, Go, Java, Rust, Ruby, Kotlin, Swift, PowerShell, and C++. DO NOT USE FOR: real line/branch/Cobertura data, coverage-backed test priorities, CRAP risk, or grading existing tests.
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。
Validates custom dotnet new templates for correctness before publishing. Catches missing fields, parameter bugs, shortName conflicts, constraint issues, and common authoring mistakes that cause templates to fail silently. USE FOR: checking template.json files for errors before publishing or testing, diagnosing why a template doesn't appear after installation, reviewing template parameter definitions for type mismatches and missing defaults, finding shortName conflicts with dotnet CLI commands, validating post-action and constraint configuration. DO NOT USE FOR: finding or using existing templates (use template-discovery), creating projects from templates (use template-instantiation), creating templates from existing projects (use template-authoring).
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。
Audits .NET test mock usage by tracing each mock setup through the production code's execution path to find dead, unreachable, redundant, or replaceable mocks. Use when the user asks to audit mock usage, find unused or unnecessary mock setups, check if mocks are needed, reduce mock duplication or over-mocking, simplify test setup, or review whether mock configurations like ILogger/IOptions should use real implementations instead. Supports Moq, NSubstitute, and FakeItEasy.
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。
Run one unattended IDEATION iteration of the quality-assurance loop — find the highest-value untested behavior in the codebase, judge it against the QA value bar, and file ONE locked `qa` issue specifying the test to write. Never writes code or tests; the next-qa skill builds from the queue this skill fills. Use when the user says "QAアイデア", "next qa idea", or wants the QA backlog refilled without implementation.
Finding validation before writing any report — 7-Question Gate (all 7 questions), 4 pre-submission gates, always-rejected list, conditionally valid with chain table, CVSS 3.1 quick reference, severity decision guide, report title formula, 60-second pre-submit checklist. Use BEFORE writing any report. One wrong answer = kill the finding and move on. Saves N/A ratio.
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。
Finding validation before writing any report — 7-Question Gate (all 7 questions), 4 pre-submission gates, always-rejected list, conditionally valid with chain table, CVSS 3.1 quick reference, severity decision guide, report title formula, 60-second pre-submit checklist. Use BEFORE writing any report. One wrong answer = kill the finding and move on. Saves N/A ratio.
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。
Client-facing red-team deliverable format — codifies the Subject / Observations / Description / Impact / Recommendation / PoC structure used for external red-team engagements (not bug-bounty platform reports). Different audience, different tone, different cadence. Built from an authorized engagement deliverable where 14 findings were packaged into a 52KB MD + 2.2MB DOCX with 16 embedded screenshots. Use when the engagement is "external red team for an enterprise client" (not H1/Bugcrowd/Intigriti), when generating the final report, when the client has specified a custom report format, or when packaging findings into DOCX/PDF.
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。