1.1万 件 ・ 関連度順
概要と使いどころ
Create production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.
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Applies principles from Robert C. Martin's 'Clean Code'. Use this skill when writing, reviewing, or refactoring code to ensure high quality, readability, and maintainability. Covers naming, functio...
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。
CloudFormation template optimization, nested stacks, drift detection, and production-ready patterns. Use when writing or reviewing CF templates.
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 production-ready Web3 applications, smart contracts, and decentralized systems. Implements DeFi protocols, NFT platforms, DAOs, and enterprise blockchain integrations.
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。
Bash scripting workflow for creating production-ready shell scripts with defensive patterns, error handling, and testing.
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 Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
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。
Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start opt...
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 Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.
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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations.
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Design, audit, and improve analytics tracking systems that produce reliable, decision-ready 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。
Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.
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 configuration loading, config schema and defaults, Viper-backed config formats, config dump behavior, vim syntax generation, template validation, prompt guideline sync, documentation under README/IDP/server docs, config converters, and generated documentation or syntax artifacts.
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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。
Use when validating a packaged build of this Hydrolix Grafana datasource plugin against Grafana's official plugin-validator — the pre-release gate that catches missing metadata, unsigned/mis-signed archives, non-executable backend binaries, and packaging errors. Builds the plugin, zips `dist/` under the plugin ID, and runs `@grafana/plugin-validator` (npx, or docker as fallback). Apply for "validate the plugin", "is this zip release-ready", or before publishing / submitting a release 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。
Read the Hot Sheet worklist and work through the current priority items
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Read the latest Glassbox code review and apply all feedback annotations
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。
Prep apple-fm for a major release — refresh the README so it advertises the current feature set, and review/revise the demo modes (the user captures the screenshots)
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Check code for standardization, readability, maintenance complexity, and defensive coding practices
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Act as FriendlyBet's CEO and primary front door for every FriendlyBet request through automatic company preflight. Own end-to-end routing, planning, execution coordination, department orchestration, decision-rights enforcement, quality gates, board-style reporting, and escalation only for strategic, legal, brand, cost, risk, or taste decisions. Use by default in FriendlyBet threads, with full department planning for broad, ambiguous, strategic, cross-functional, or outcome-driven requests such as SEO, new features, multi-sport expansion, product direction, release execution, company operations, or agent coordination.
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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.
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Review FriendlyBet quality, regression risk, test plans, release readiness, version bump discipline, scoring/locking correctness, provider fallback behavior, and dirty-worktree safety. Use before shipping app code, scoring changes, migrations, sports integrations, copy updates, PWA cache changes, or any risky user-facing flow.
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。
Validate sequencing and cross-layer readiness before phase slicing, including coverage and consistency hard 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。
Orchestrate phase validation across code-quality and production-readiness gates with mandatory reporting and verdicting
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Transforms user prompts into optimized prompts using established frameworks (RTF, RISEN, Chain of Thought, RODES). Analyzes intent, selects framework, and produces structured, ready-to-use prompts.
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。