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概要と使いどころ
Read and manage email via IMAP (ProtonMail Bridge, Gmail, etc.). Check for new/unread messages, fetch content, search mailboxes, and mark as read/unread. Works with any IMAP server including ProtonMail Bridge.
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 monitor brand mentions, detect trademark infringement, or set up brand monitoring. Also use when the user mentions "brand monitoring," "brand watch," "trademark watch," "brand mentions," "impersonation detection," "counterfeit detection," or "brand abuse monitoring." For enforcement, use brand-protection.
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 create sales collateral, pitch decks, one-pagers, objection handling docs, or demo scripts. Also use when the user mentions 'sales deck,' 'pitch deck,' 'one-pager,' 'leave-behind,' 'objection handling,' 'deal-specific ROI analysis,' 'demo script,' 'talk track,' 'sales playbook,' 'proposal template,' 'buyer persona card,' 'help my sales team,' 'sales materials,' or 'what should I give my sales reps.' Use this for any document or asset that helps a sales team close deals. For competitor comparison pages and battle cards, see competitor-alternatives. For marketing website copy, see copywriting. For cold outreach emails, see cold-email.
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。
Triage an email inbox — "triage my inbox", "sort my inbox", "what emails need a reply", "clear my inbox". Governs the Gmail or Workspace connector you already have rather than shipping its own 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。
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered 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。
Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
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。
Himalaya CLI: IMAP/SMTP email from terminal.
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 the full Forge pipeline unattended: each phase is reviewed by a fresh evaluator subagent, the findings feed back, and the run advances itself. Use when the user runs /forgemaster-auto or wants a feature built end to end without approval gates.
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 a task by complexity and run the gated Forge pipeline (research → plan → implement → ship). Use when the user runs /forgemaster or wants the full guided feature pipeline.
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。
Trimmed Forge pipeline (scope → build → wrap) for small, clear-scope work. Use when the user runs /forgemaster-mini or has a small, well-scoped 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。
Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similarity search. Use PROACTIVELY for vector search implementation, embedding optimization, or semantic retrieval systems.
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。
Skill for graphql-schema-design tasks.
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。
Test Data Builder Pattern complete implementation guide. Used when using builder pattern to create maintainable test data or simplify complex object test preparation. Covers fluent interface, semantic methods, default value design, and Builder composition patterns. Keywords: test data builder, builder pattern test, test data builder, object mother, fluent interface, fluent interface, UserBuilder, ProductBuilder, .With(), .Build(), AUser(), test data preparation, complex object creation, semantic testing
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Complete guide for AutoFixture and Bogus integration. Use when you need to combine AutoFixture with Bogus to generate test data that is both anonymous and realistic. Covers SpecimenBuilder integration, hybrid generators, test data factories, and circular reference handling. Keywords: autofixture bogus integration, autofixture bogus, bogus integration, Faker, EmailSpecimenBuilder, PhoneSpecimenBuilder, NameSpecimenBuilder, realistic test data, semantic data, hybrid generator, HybridTestDataGenerator, OmitOnRecursionBehavior, circular reference
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。
Integrates AI/LLM via Semantic Kernel. Plugins, prompt templates, memory stores, agents.
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。
Using AutoFixture to automatically generate test data basic skill. Used when quickly generating test objects, reducing boilerplate code, and implementing anonymous testing. Covers Fixture.Create, CreateMany, circular reference handling, and xUnit integration. Keywords: autofixture, fixture, auto-generate test data, test data generation, anonymous testing, anonymous testing, fixture.Create, CreateMany, fixture.Build, Create<T>, AutoFixture.Xunit2, OmitOnRecursionBehavior, IFixture, generate test data, generate test data
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。
Using Bogus to generate realistic fake data specialized skill. Used when generating realistic names, addresses, phone numbers, emails, company info and other test data. Covers Faker class, multi-language support, custom rules, bulk data generation, etc. Keywords: bogus, faker, fake data, fake data, realistic data, realistic data, fake name, fake address, fake email, Faker<T>, RuleFor, Generate, faker.Name, faker.Address, faker.Internet, generate fake data, generate fake data, seed data
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 a page or the whole yoursite site (or a new site) for indexing readiness — cache headers, sitemap, robots, canonical, JSON-LD, internal links — and check the publish pipeline (Cloudflare purge/warm, IndexNow, GSC, Bing). Use before/after publishing content or launching a site.
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 auditing or improving example.com's SEO/indexing — Google Search Console issues (404s, sitemap, "discovered not indexed"), on-page checks (title/meta/canonical/OG/H1/internal links), or wiring search-engine notification (IndexNow/GSC/Bing/Yandex). Also use when the operator pastes GSC findings and asks to fix + validate.
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。
Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.
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。
Parse Office 365 Unified Audit Logs via Microsoft Graph API to detect email forwarding rule creation, inbox delegation, suspicious OAuth app grants, and other indicators of account compromise.
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Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment 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。
Improve search engine visibility with proper meta tags, structured data, sitemaps, and semantic HTML.
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。
Plan and synthesize a source-grounded multi-paper literature review. Use for systematic literature reviews, survey matrices, inclusion/exclusion criteria, research gaps, or "review the literature on X" requests; do not use for reviewing one paper, ordinary web summaries, citation formatting only, or medical/legal conclusions.
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。