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「databases」の検索結果

569 件 ・ 関連度順

概要と使いどころ

Configure and manage Supabase projects using MCP (Model Context Protocol). Use this skill when working with Supabase databases, setting up MCP servers, designing database schemas, implementing Row Level Security, managing migrations, or building modern data architectures with PostgreSQL. Essential for Supabase development, database design, and AI-powered database operations.

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。

tdimino/claude-code-minoan412026年9月28日 更新

Academic research skill for Biblical Hebrew, Semitic linguistics, cuneiform studies, and comparative Ancient Near Eastern research. Provides Sefaria API for Hebrew Bible, CDLI/ORACC for cuneiform databases, and web discovery via Omnisearch, Exa, Firecrawl, and Obscura for finding scholarly sources across JSTOR, Perseus, Persée, Google Scholar, and academia.edu. Triggers on Hebrew quotes, cuneiform, Sefaria, ANE research, Minoan, search for scholarship, find papers, literature review, scholarly search, academic search, Genesis/Tehom, Ugaritic, Talmudic sources, extract from PDF, OCR academic.

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。

tdimino/claude-code-minoan412026年9月28日 更新

Configure and manage MCP (Model Context Protocol) servers in Claude Code CLI. Use this skill when adding, removing, listing, or troubleshooting MCP servers, or when questions arise about MCP configuration, transport types, scopes, or authentication. Essential for connecting Claude Code to external tools, databases, and APIs.

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。

tdimino/claude-code-minoan412026年9月28日 更新

Record insect sightings with location, date, habitat, photography, behavior notes, preliminary identification, and citizen science submission. Covers GPS coordinates, weather conditions, microhabitat description, macro photography techniques, behavioral observations, preliminary identification to order using body plan, and submission to citizen science platforms such as iNaturalist. Use when encountering an insect you want to document, contributing to citizen science biodiversity databases, building a personal observation journal, or supporting ecological surveys with georeferenced photographic records.

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。

pjt222/agent-almanac372026年10月13日 更新

Achieve distributed agreement without central authority using bee democracy, threshold voting, and quorum sensing. Covers proposal generation, advocacy dynamics, commitment thresholds, deadlock resolution, and consensus quality assessment. Use when a group must decide between options without a designated leader, when centralized decision-making is a bottleneck, when stakeholders have different perspectives to integrate, or when designing automated systems that must reach consensus such as distributed databases or multi-agent AI.

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。

pjt222/agent-almanac372026年10月13日 更新

Fix RFDB V2 graph data silently not persisting to disk after analysis. Use when: (1) rfdb-server reports "0 nodes, 0 edges" on restart despite successful analysis, (2) segment directories exist but are empty (no .bin files), (3) manifest_index.json shows total_nodes: 0 despite analysis logging 70k+ nodes, (4) Docker builds produce empty graph databases, (5) --clear flag used before analyze command. Root cause: GraphEngineV2::clear() replaces the store with MultiShardStore::ephemeral() which has path: None, causing all flush operations to write to in-memory buffers only.

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。

Disentinel/grafema362026年8月24日 更新

chdb-sql

無料

Use when the user wants to run SQL - especially analytical SQL - on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB - embedded ClickHouse SQL in Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window functions, windowFunnel, geoToH3, JSON path ops, Session, parametrized queries); imports `chdb` or calls `chdb.query()`. SKIP this skill for pandas-style DataFrame method-chaining (use chdb-datastore instead) or ClickHouse server 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。

cline/plugins352026年9月19日 更新

oracledb

無料

Use these skills to manage and monitor Oracle databases by executing SQL statements, exploring schema metadata, analyzing query performance, monitoring active sessions and resource consumption, and managing storage and object health.

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。

cline/skills352026年7月21日 更新

Operate Railway infrastructure: sign up for or sign in to a Railway account, create projects, provision services and databases, manage object storage buckets, deploy code, configure environments and variables, manage domains, troubleshoot failures, check status and metrics, set up Railway agent tooling, and query Railway docs. Use this skill whenever the user mentions Railway, signing up, creating an account, registering, logging in, deployments, services, environments, buckets, object storage, build failures, agent setup, MCP, or infrastructure operations, even if they don't say "Railway" explicitly. Also invoke this skill when the user asks to be signed up, registered, or onboarded to Railway: do not refuse — drive them through the unauthed `railway up` flow (deploys + signs up on the fly) or `railway login` (which creates new accounts on the fly).

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。

cline/skills352026年7月21日 更新

bun

無料

Bun runtime, package manager, bundler, and test runner. Use when running scripts with bun, managing packages, serving HTTP with Bun.serve, querying databases with Bun.sql/bun:sqlite/Bun.redis, shell scripting with $, using S3/file I/O, writing tests with bun:test, bundling or compiling to executable, or using any Bun-specific API (spawn, glob, semver, FFI, workers, plugins, HTMLRewriter).

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。

fellipeutaka/kanpeki332026年8月28日 更新

axi

無料

Agent eXperience Interface (AXI) router — the main entry point for agent-ergonomic CLIs. Use whenever the agent needs GitHub, browser automation, human review, quota routing, Slack, Notion, AWS/Docker/K8s, databases, GitLab (glab-axi), Oracle DB (oracle-axi), tmux/herdr/WezTerm sessions (cyber-mux), or any AXI-catalog tool; when choosing AXI vs MCP vs raw CLI; when building or reviewing an agent-facing CLI; or when the user says axi, gh-axi, chrome-devtools-axi, TOON output, agent ergonomics, or "prefer AXI". When in doubt about which external tool interface to use, start here.

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。

MoizIbnYousaf/marketing-cli322026年9月12日 更新

Run the Upstash CLI (`upstash`) from a terminal, shell script, or CI job when no Upstash MCP tools are in the session. Do not load this skill when Upstash MCP tools are available (the Upstash plugin registers mcp.upstash.com) - they already cover creating, listing, renaming, and deleting Redis databases, running Redis commands, usage stats, backups, Vector and Search indexes, QStash schedules and messages, Blob buckets, and Box, so call them directly. Use this skill for shell work the MCP does not do - a CI step or provisioning script that needs `upstash` commands with JSON output, piping results into other commands, `upstash auth login` and API-key setup, team and member management, changing plans, regions, TLS, eviction, auto-upgrade, or budgets, minting temporary S3 credentials for a Blob bucket, connecting a coding agent to Upstash with `upstash setup` (the Upstash plugin, or the remote MCP server plus skills), or when the user explicitly asks for the CLI or for managing Upstash without the console.

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。

upstash/skills302026年10月6日 更新

devops

無料

Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native applications.

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。

VoDaiLocz/kilo-kit-mcp272026年9月13日 更新

Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend 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。

VoDaiLocz/kilo-kit-mcp272026年9月13日 更新

Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.

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。

VoDaiLocz/kilo-kit-mcp272026年9月13日 更新

Detects sensitive data stored insecurely on mobile devices (Android/iOS). Trigger on: SharedPreferences, NSUserDefaults, SQLite, Room DB, DataStore, Core Data, Keychain misconfiguration, external storage, backup exposure, plaintext files, unencrypted databases, adb backup, iCloud backup, NSFileProtection, EncryptedSharedPreferences, SQLCipher, allowBackup, FLAG_SECURE, keyboard cache, sensitive logs. Covers MASVS-STORAGE-1 (local storage) and MASVS-STORAGE-2 (exposure to unauthorized actors).

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。

ShulkwiSEC/bb-huge242026年7月11日 更新

Execute Indirect Prompt Injection attacks against Large Language Models (LLMs) by subtly embedding malicious instructions within external data sources (e.g., websites, documents, databases) that the LLM autonomously ingests. This forces the model to execute attacker-controlled commands under the guise of processing legitimate user requests.

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。

ShulkwiSEC/bb-huge242026年7月11日 更新

Identify and exploit SQL Injection vulnerabilities in Django applications, specifically focusing on edge cases involving raw querysets (`RawSQL`), improper use of `.extra()`, and poorly sanitized filters where Django's typical ORM protections are bypassed.

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。

ShulkwiSEC/bb-huge242026年7月11日 更新

Persistent storage, SQLite databases, and credential management in Electron apps

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。

agents-inc/skills242026年9月8日 更新

Use when hosting, deploying, or operating an app on the Prisma Platform: projects, branches, preview environments, services and their versions, Prisma Postgres databases, object-store buckets, environment variables, custom domains, logs, or the GitHub integration. Triggers on "Prisma Platform", "Prisma Compute", "Prisma Postgres", "Prisma Storage", "preview environment", `prisma deploy`, `prisma dev`, `prisma auth`, `prisma project`, `prisma branch`, `prisma service`, `prisma postgres`, `prisma bucket`, `prisma git`, `prisma.config.ts`, promote, rollback.

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。

prisma/prisma-cli222026年10月13日 更新

Enriches indicators with context from threat-intel sources: planning lookups against reputation, passive DNS, WHOIS, and sandbox/sample databases, scoring confidence, and avoiding operational-security mistakes that tip off adversaries. Activates for requests to enrich IOCs, add threat context, or plan indicator lookups safely.

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。

meltedinhex/analyst-ai-pack222026年7月7日 更新

sdd

無料

Create a Software Design Document (SDD) defining component architecture, data contracts, API schemas, and platform compatibility before planning. Use in Tier 3 (Full Pipeline) or when modifying interfaces, hooks, databases, or multi-platform contracts.

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。

datit309/supergraph222026年10月13日 更新

Product marketing and go-to-market strategy for B2B SaaS launches and positioning. Use this skill when planning a product launch, developing positioning and messaging, analyzing competitive landscape, building customer advocacy programs, designing a customer referral program (who may accept the reward, how the introduction is made), designing a win/loss interview program, working out why we lose deals, designing GTM strategy, creating category positioning, planning analyst briefings, or deciding which country to expand into and how far to localize. Also use it for an early-stage startup where the founder is still doing the selling — running founder-led sales, setting up a design-partner program, judging whether you have product-market fit, deciding what not to do yet, deciding when to hire the first AE or first marketer, and moving upmarket to larger buyers. Also use it when your company has just acquired another (or is about to), to plan the marketing integration: what you may and may not do between signing and close, the first letter to the acquired customers, whether to keep, endorse, fold in or retire the acquired brand, merging the two marketing databases without mailing people who opted out, when to start cross-selling, and announcing a product sunset. Also use it to design a demand-generation campaign and the channel plan it runs on: one campaign with one job, the offer for buyers who are and are not in market, what each channel is for, the kill and scale rules set before launch, the follow-up sales agrees to, the yearly calendar of always-on programs and tentpole campaigns, and which channels to keep, test or stop. Also use it for brand marketing and demand creation — how much to spend on brand versus performance, what to measure when a brand campaign produces no conversion event, and how to answer "we cannot attribute it". Also triggers on: founder-led sales, founder-led GTM, design partners, design partner agreement, first customers, first 10 customers, do we have product-market fit, PMF, Sean Ellis test, very disappointed survey, pre-seed, seed stage, when to hire our first AE, first sales hire, first marketing hire, moving upmarket, going upmarket, enterprise readiness, first enterprise deal, what do enterprise buyers need before they sign, positioning, product launch, beta program, early access program, design partners, private preview, public preview, general availability, GA launch, when can we call it GA, can sales sell a beta feature, selling the roadmap, launch tier, competitive intelligence, messaging, customer advocacy, win/loss analysis, win/loss interviews, why we lose deals, closed-lost analysis, loss reason, close-reason field, competitive displacement, displace an incumbent, rip and replace, competitive takeout, switch from a competitor, win deals from a competitor, incumbent contract, renewal window, auto-renewal notice period, switching costs, EU Data Act, cloud switching rights, why do we lose to no decision, GTM, category design, ideal customer profile, ICP, what is our real ICP, who actually buys from us, refresh our ICP from closed-won deals, ICP refresh before planning, analyst briefing, G2 review, international expansion, market entry, expand into Europe, which country should we launch in next, localization, translate our site, in-country go-to-market, regional GTM, is cold email legal in Germany, brand marketing, brand awareness, brand vs performance, brand versus demand gen, demand creation, demand capture, 95-5 rule, out of market buyers, category entry points, distinctive brand assets, mental availability, brand tracking, brand health, brand lift, share of search, how do we measure brand, justify brand spend, brand budget. Also triggers on public-sector marketing: sell to government, government marketing, public sector go-to-market, federal marketing, state and local government, SLED, FedRAMP, FedRAMP marketing claims, can we say FedRAMP ready, GovRAMP, StateRAMP, VPAT, accessibility confor

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。

shalintripathi/saas-marketing-agents212026年10月13日 更新

Query the Ensembl REST API for regulatory feature annotations, variant effect prediction (VEP), coordinate liftover, gene lookups, and cross-references. Use when the user needs to annotate variants with VEP (consequence, CADD, REVEL, SpliceAI), check Ensembl Regulatory Build overlap for ENCODE regions, convert coordinates between GRCh37 and GRCh38, resolve gene IDs (Ensembl ↔ symbol ↔ RefSeq), look up gene phenotype associations, or cross-reference ENCODE targets with Ensembl annotations. Also use when the user mentions Ensembl, VEP, variant effect predictor, liftover, assembly conversion, regulatory build, gene lookup, or cross-references between databases.

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。

ammawla/encode-toolkit212026年9月27日 更新