「database」の検索結果

This skill helps users automatically find social media profiles across platforms like Facebook, Twitter, Instagram, LinkedIn, etc. using the BrowserAct API. Agent should proactively apply this skill when users express needs like finding someone's social media accounts, discovering a brand's social media presence, tracking down social profiles of job candidates, finding contact info for sales prospects, researching a person's digital footprint, verifying the identity of someone met online, monitoring the social media reach of influencers, checking social accounts of business competitors, gathering public profiles for background research, locating official customer service accounts across platforms, or compiling contact databases for networking.

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Use when designing, implementing, debugging, or reviewing Nexent relational schemas, FastAPI endpoints, backend services, database access, SQL migrations, or backend/SDK configuration. Includes table/field naming, types, JSONB boundaries, audit fields, keys, and indexes even before code paths exist. Skip frontend-only work and unrelated SDK algorithms.

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 or scaffold ASP.NET Core code — Razor Pages, Blazor components, MVC controllers, views, and Minimal API endpoints — without using ASP.NET Core CLI scaffolding/code-generation tools. Use when (1) adding CRUD pages, views, or API endpoints backed by Entity Framework (EF Core) and a database, (2) generating code to create, read, update, and delete data using a DbContext, (3) scaffolding UI components that match the project's existing CSS framework and coding patterns, or (4) creating data-driven forms, tables, and navigation for a model class. Do not use for non-ASP.NET projects or when CLI-based scaffolding is preferred.

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Help users chaos test their app with mirrord: inject artificial latency or connection errors into a mirrord session's outgoing traffic via per-session chaos rules managed with the `mirrord chaos` CLI. Use when a user wants to add latency or delay to outgoing connections or a dependency (e.g. a slow database), simulate connection failures (reset, timed out, refused), test app behavior under degraded network conditions, or wire chaos rules into CI test runs. Always use this skill instead of the deprecated _experimental_.latency mirrord config option.

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 edit Obsidian Bases (.base files) with views, filters, formulas, and summaries. Use when working with .base files, creating database-like views of notes, or when the user mentions Bases, table views, card views, filters, or formulas in Obsidian.

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。

Scaffold, extend, and verify reactive local-first JavaScript or TypeScript applications with TinyBase. Use when choosing TinyBase for in-memory tabular or key-value state, generating an app with create-tinybase, adding schemas or UI bindings, resolving TinyBase import paths, configuring browser or database persistence, configuring MergeableStore synchronization over WebSockets or Cloudflare Durable Objects, or diagnosing an existing TinyBase application.

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。

Hunt vector-store / embedding-layer weaknesses in RAG pipelines (OWASP LLM08 Vector and Embedding Weaknesses) — persistent corpus poisoning that survives across sessions and users (distinct from one-shot indirect prompt injection, which is owned by hunt-llm-ai), cross-tenant vector-database IDOR (unauthenticated or unscoped queries against Pinecone/Weaviate/Chroma/Milvus/Qdrant/pgvector), source-text/metadata leakage in similarity-search results, and retrieval-hijack via adversarial embedding proximity ('SEO poisoning' for RAG). Targets: any app with a shared knowledge base, document upload feeding a chatbot, or a directly reachable vector-DB port. Validate: a second, clean session/account must inherit a poisoned result, or a cross-tenant artifact must be independently verifiable — confabulation is not a finding, same bar as hunt-llm-ai. Use when target is RAG-backed, exposes a vector-DB port, or lets users upload documents that other users' queries later retrieve.

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, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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。

Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

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。

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

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 hexagonal architecture in the Rust backend. Use before modifying crates/ or Rust services, especially inbound axum/tool/listener adapters, domain services/ports, outbound adapters, authorization, permissions, database access, or external clients.

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 SQLx migration files with `sqlx migrate add <name>`. Use when asked to add, create, or generate a sqlx/sqlx-cli database migration.

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 hexagonal architecture in the Rust backend. Use before modifying crates or Rust services, especially inbound axum/tool/listener adapters, domain services/ports, outbound adapters, authorization, permissions, database access, or external clients.

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 edit Obsidian Bases (.base files) with views, filters, formulas, and summaries. Use when working with .base files, creating database-like views of notes, or when the user mentions Bases, table views, card views, filters, or formulas in Obsidian.

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。

Diverga v12.0 setup wizard. 4-step researcher profile setup. Captures discipline, experience, tools, database access, and Agent Teams + VS Arena preference. Triggers: setup, configure, 설정, install

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 if medicinal chemistry papers are in ChEMBL database to access curated bioactivity 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。

Generate a complete academic literature survey from scratch using multi-agent orchestration. Searches academic databases (OpenAlex, CrossRef, Unpaywall), downloads PDFs, builds BibTeX, drafts a LaTeX review, compiles it, reviews for quality, and revises based on feedback — all automated. Use this skill whenever the user asks to "generate a literature review", "write a survey paper", "review recent papers on [topic]", "create a survey of [field]", "综述", "文献综述", "survey papers in top journals", or wants a multi-agent pipeline to produce a publishable-quality literature review. Also trigger when the user wants to search multiple journals for papers on a topic and synthesize findings into a structured document. Works for any academic field but optimized for economics journals.

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。

Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.

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, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

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。

Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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Administers Observal users, settings, diagnostics, review queues, security events, audit logs, SAML, SCIM, the local Observal server, its upgrades and rollback, and its own PostgreSQL and ClickHouse schema migrations. Use when the user needs privileged governance, submission decisions, identity configuration, security investigation, or Observal server operations. Not for querying a database or any work outside Observal administration.

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 starting any task the organization may already have an approved skill, prompt, MCP server, or Agent for: reviewing code, a commit, a diff, or a pull request; writing tests or documentation; querying a database, API, or service; automating a browser or web page; running untrusted code; connecting to a SaaS tool; drafting, researching, or any other substantive work. The user will not mention Observal: the task type is the trigger. Check what is already installed, then run observal discover search as the first action, before reading the repository or working from scratch. Also use when the user wants to log in, configure Observal, inspect local harness setup, share or open a repository Agent share, manage a teamspace or invitation, process inbox items, check installed registry items, or call an endpoint without a dedicated command.

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。