2.3万 件 ・ 関連度順
概要と使いどころ
Opinionated backend development standards for Node.js + Express + TypeScript microservices. Covers layered architecture, BaseController pattern, dependency injection, Prisma repositories, Zod valid...
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。
Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations.
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。
How to use a Win32 build of BusyBox to run many of the standard UNIX command line tools on Windows.
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。
Hard-edged writing style contract for timeless, forceful English prose without AI tics
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。
Orchestrate end-to-end backend feature development from requirements to deployment. Use when coordinating multi-phase feature delivery across teams and services.
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。
Azure Key Vault Secrets SDK for Rust. Use for storing and retrieving secrets, passwords, and API keys. Triggers: "keyvault secrets rust", "SecretClient rust", "get secret rust", "set secret rust".
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。
Azure Key Vault Secrets Java SDK for secret management. Use when storing, retrieving, or managing passwords, API keys, connection strings, or other sensitive configuration 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。
Build call automation workflows with Azure Communication Services Call Automation Java SDK. Use when implementing IVR systems, call routing, call recording, DTMF recognition, text-to-speech, or 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。
Azure AI Document Translation SDK for batch translation of documents with format preservation. Use for translating Word, PDF, Excel, PowerPoint, and other document formats at scale.
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。
Transform audio recordings into professional Markdown documentation with intelligent summaries using LLM 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。
Optimal ViewModel and Wizard creation patterns for Avalonia using Zafiro and ReactiveUI.
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。
Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates 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。
Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.
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。
Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
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。
Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.
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 for Nauthilus Redis client, Redis Cluster/Sentinel/topology behavior, Redis-backed token/session/flow/cache/bruteforce state, Lua Redis scripts, `NOSCRIPT` recovery, script upload/retry behavior, redismock tests, local cache coordination, and fail-closed runtime state changes.
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 running the dev Grafana stack and/or the Playwright e2e suite against a *packaged* plugin zip (a release/RC artifact like `hydrolix-hydrolix-datasource-<ver>.zip`) rather than the working-tree `dist/`. Unpacks the package into a timestamped `dist_<timestamp>/dist` sandbox alongside copies of the compose artifacts, so the run is reproducible and the folder stays available to experiment with afterwards. Delegates stack bring-up to `stack-run` (frozen mode: read-only mount + `DEV=false` so the mage-watcher can't rebuild the packaged Go binary), verifies signature/version, runs the suite, and treats cleanup as optional — the sandbox is deleted only with the user's approval. Apply whenever the task is "test this plugin package / zip" or "run e2e against the built artifact".
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。
Review FriendlyBet privacy, RLS security, auth, recovery codes, session storage, data minimization, public snapshots, share surfaces, legal/gambling wording, real-money risk, and compliance-sensitive product changes. Use when a task changes data access, user identity, public sharing, money-like language, security posture, or legal risk.
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。
Control FriendlyBet operating cost, free-tier viability, provider/API cost, GitHub Actions/Supabase/Vercel usage, documentation hygiene, company memory updates, playbook maintenance, and skill validation. Use when evaluating cost, operational burden, tooling, internal docs, company memory, or whether agent profiles should become full skills.
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。
Review or design FriendlyBet user experience, visual direction, mobile-first flows, premium sports interface, Hebrew/English copy fit, RTL behavior, accessibility, interaction patterns, and product UI polish. Use when a task touches screens, flows, layout, visual hierarchy, onboarding, prediction UX, share UX, or design quality.
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。
Coordinate FriendlyBet company-level strategy, CEO handoff, department orchestration, HR/agent-quality escalation, operating-model decisions, multi-agent synthesis, roadmap tradeoffs, decision rights, quality gates, and updates to the virtual company system. Use when Eyal asks to involve the company, CEO, leadership, strategy, operations, several departments, or named executive agents such as Strategy Director, Chief of Staff, or Operating System Lead.
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 FriendlyBet ethical growth, SEO, README positioning, open-source contribution paths, self-hosting story, public trust, and discovery without ads, trackers, spam, or dark patterns. Use for repo-facing docs, growth strategy, launch positioning, SEO pages, contributor onboarding, or public messaging.
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。
Shape FriendlyBet product decisions, MVP scope, user stories, tournament flows, multi-sport expansion, pool mechanics, social competition loops, and feature prioritization. Use when planning what FriendlyBet should build, cut, sequence, or validate, especially for new sports, prediction formats, pool flows, leaderboards, sharing, or product strategy.
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。
Govern FriendlyBet agent values, professional standards, anti-hallucination behavior, truthfulness, risk reporting, AI resource discipline, feedback loops, skill improvement, performance reviews, decision-rights hygiene, and team quality. Use when creating, reviewing, promoting, correcting, or retiring agents; reducing hallucinations or mistakes; reviewing AI/tool usage; handling agent incidents; or aligning work with Eyal's philanthropic user-first approach.
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。