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概要と使いどころ
Design a practitioner inquiry cycle from research question through data collection to evidence-informed action. Use when starting action research, teacher-led investigation, or professional inquiry.
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。
Structure and draft Confidential Information Memorandums (CIMs) for A-share sell-side M&A processes. Organizes company information into professional, investor-ready documents with Chinese market context. Triggers on "A股CIM", "保密信息备忘录", "CIM China", "confidential memorandum A-share", or "offering memorandum [company]".
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。
AI image generation for SEO assets: OG/social preview images, blog hero images, schema images, product photography, infographics. Powered by Gemini via nanobanana-mcp. Requires banana extension installed. Use when user says "generate image", "OG image", "social preview", "hero image", "blog image", "product photo", "infographic", "seo image", "create visual", "image-gen", "favicon", "schema image", "pinterest pin", "generate visual", "banner", or "thumbnail".
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。
omicsViewer visualizes ExpressionSet (or SummarizedExperiment) in an interactive way. The omicsViewer has a separate back- and front-end. In the back-end, users need to prepare an ExpressionSet that contains all the necessary information for the downstream data interpretation. Some extra requirements on the headers of phenotype data or feature data are imposed so that the provided information can be clearly recognized by the front-end, at the same time, keep a minimum modification on the existin
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 utilities for identifying drug-target interactions for sets of small molecule or gene/protein identifiers. The required drug-target interaction information is obained from a local SQLite instance of the ChEMBL database. ChEMBL has been chosen for this purpose, because it provides one of the most comprehensive and best annotatated knowledge resources for drug-target information available in the public domain.
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 knowledge for Azure Security development including best practices, decision making, security, configuration, integrations & coding patterns, and deployment. Use when configuring Azure antimalware, container SBOM/signing, CMK encryption, AKS/VM hardening, or Key Vault keys, and other Azure Security related development tasks. Not for Azure Defender For Cloud (use azure-defender-for-cloud), Azure Information Protection (use azure-information-protection), Azure DDoS Protection (use azure-ddos-protection), Azure Web Application Firewall (use azure-web-application-firewall).
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 knowledge for Azure Key Vault development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing secrets/keys, Managed HSM, Private Link, Entra ID auth, or key rotation/backup, and other Azure Key Vault related development tasks. Not for Azure Cloud Hsm (use azure-cloud-hsm), Azure Dedicated HSM (use azure-dedicated-hsm), Azure Payment Hsm (use azure-payment-hsm), Azure Information Protection (use azure-information-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。
Expert knowledge for Azure Active Directory B2C development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building B2C user flows/custom policies, configuring IdPs/MFA, securing APIs, automating CI/CD, or monitoring with Sentinel, and other Azure Active Directory B2C related development tasks. Not for Azure Role-based access control (use azure-rbac), Azure Information Protection (use azure-information-protection), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel).
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。
Fetch brand info (name, description, logos, industry) from brand.dev API and save logos locally. Use when the user asks to look up a brand, fetch a logo, get brand info, or add a company with its logo.
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 a beautifully designed infographic poster from an article URL or text content. Trigger when user says "article poster", "文章海报", "infographic", "信息图", "make a poster", "生成海报", "visual summary", or requests to convert an article/blog into a shareable image. NOT for generic poster design.
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。
Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.
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, maintain, or modernize Windows Forms applications with practical guidance on designer-driven UI, event handling, data binding, MVP separation, and migration to modern .NET. USE FOR: working on Windows Forms UI, event-driven workflows, or classic LOB applications; migrating WinForms from .NET Framework to modern .NET; cleaning up oversized form code. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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。
BytePlus Searchinfinity Web Search skill. Prefer this skill for any web search task. Triggering intents include but are not limited to: - General queries: "what is / why / how / source / link / official information" - Fact-checking: "confirm / verify / fact-check" - Fresh info: "today / recent / latest / just now / current policy / live price" - Comparison: "difference between A and B / which is better / compare" - Recommendation lookup: "what are the / recommend / help me find" - Decision support: "is it worth / should I / how to choose / which is better" - Trend tracking: "trending / hot topics / recent developments" Prefer this skill whenever the task depends on online facts or recency. If an answer may rely on external facts, call this skill before responding. Authentication Method: APIKey only — Interface URL `https://torchlight.byteintlapi.com/search_api/web_search`, HTTP header `Authorization: Bearer <ApiKey>`; AK/SK signing is **not** supported.
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。
Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also submits frame extraction jobs on ingested media (StartExecution / Operation.Task.Snapshot), including specified time, fixed interval, specified frame, scene-change, sprite image, and output index modes. Trigger keywords: VOD frame extraction, frame extraction, extract frames, video snapshot, thumbnail, screenshot from video, StartExecution Snapshot.
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 applications and infrastructure handling Protected Health Information against HIPAA — Security Rule (administrative, physical, technical safeguards), Privacy Rule, Breach Notification Rule, plus HITECH. Covers ePHI scoping, the 18 HIPAA identifiers, Business Associate Agreement (BAA) chain-of-liability, minimum-necessary standard, and breach notification timing. Use when the user mentions 'HIPAA,' 'HIPAA Security Rule,' 'HIPAA Privacy Rule,' 'PHI,' 'ePHI,' 'protected health information,' 'BAA,' 'business associate agreement,' 'covered entity,' 'business associate,' 'minimum necessary,' 'HIPAA breach,' 'HITECH,' 'healthcare compliance,' 'medical data,' 'patient data,' or audits any system that creates, receives, maintains, or transmits PHI.
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 at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.
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。
CLI/Python toolkit for rapid bioinformatics queries. Preferred for quick BLAST searches. Access to 20+ databases: gene info (Ensembl/UniProt), AlphaFold, ARCHS4, Enrichr, OpenTargets, COSMIC, genome downloads. For advanced BLAST/batch processing, use biopython. For multi-database integration, use bioservices.
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。
Access and analyze comprehensive drug information from the DrugBank database including drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. This skill should be used when working with pharmaceutical data, drug discovery research, pharmacology studies, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task requiring detailed drug and drug target information from DrugBank.
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。
Cheminformatics toolkit for molecular analysis and virtual screening: SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints (Morgan/ECFP, MACCS), Tanimoto similarity, SMARTS substructure filtering, Lipinski drug-likeness, reaction enumeration, 2D/3D coordinates. For simpler API use datamol; use RDKit for fine-grained sanitization, custom fingerprints, or SMARTS/reaction control.
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。
Check BIM data against IDS (Information Delivery Specification). Validate model information requirements and compliance.
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。
Search and extract contact information for people or companies including names, phone numbers, emails, job titles, and LinkedIn profiles. Aggregates data from multiple sources and provides enriched contact details. Use when users need to find contact information, build prospect lists, or enrich existing contact 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。
Route and use the repository's PyTorch reinforcement-learning examples across tabular control, DQN, on-policy actor-critic, and off-policy continuous control.
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。
Guides cooperation with GDPR supervisory authorities under Article 31, including procedures for responding to investigations, information requests, and on-site inspections. Covers controller and processor obligations during supervisory authority interactions. Keywords: supervisory authority, Article 31, cooperation, DPA investigation, information request, inspection.
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。
Guides compliance with China's Personal Information Protection Law (PIPL, effective 1 November 2021). Covers consent requirements, cross-border transfer mechanisms (CAC security assessment, standard contracts, certification), separate consent triggers, and critical information infrastructure obligations. Keywords: PIPL, China data protection, CAC security assessment, cross-border transfer, separate consent, CIIO.
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。