「best」の検索結果

Apply Apollo.io API security best practices. Use when securing Apollo integrations, managing API keys, or implementing secure data handling. Trigger with phrases like "apollo security", "secure apollo api", "apollo api key security", "apollo data 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。

Production-ready patterns for Apify SDK and apify-client in TypeScript. Use when building Actors with Crawlee, managing datasets/KV stores, or implementing robust client wrappers with retry and validation. Trigger with "apify SDK patterns", "apify best practices", "apify client wrapper", "crawlee patterns", "idiomatic apify".

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。

Production-grade architecture patterns for Apify-powered applications. Use when designing scraping infrastructure, building multi-Actor pipelines, or integrating Apify into a larger system architecture. Trigger with "apify architecture", "apify best practices", "apify project structure", "scraping architecture", "apify system 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。

Apply Anthropic Claude API security best practices for key management, input validation, and prompt injection defense. Use when securing API keys, validating user inputs before sending to Claude, or implementing content safety guardrails. Trigger with phrases like "anthropic security", "claude api key security", "secure anthropic", "prompt injection defense".

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。

Apply production-ready patterns for the Anima SDK design-to-code pipeline. Use when building reusable Anima client wrappers, implementing output caching, or establishing team standards for design-to-code automation. Trigger with: "anima SDK patterns", "anima best practices", "anima code patterns".

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。

Execute software engineer specializing in creating production-ready ADK agents with best practices, code structure, testing, and deployment automation. Use when asked to "build ADK agent", "create agent code", or "engineer ADK application". Trigger with relevant phrases based on skill purpose.

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。

Pythonic code with modern type hints, dataclasses, async patterns, packaging, 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。

SEO best practices for the Grida project across Next.js pages, blog posts, and documentation. Covers Next.js metadata API, Open Graph / Twitter cards, sitemaps, image search optimization, structured data (JSON-LD), Docusaurus frontmatter, and content writing for search. Use when creating or editing public-facing pages under editor/app/(www), writing blog posts, authoring docs, or reviewing SEO-related metadata. Trigger phrases: "SEO", "metadata", "sitemap", "open graph", "og image", "meta tags", "search ranking", "structured data", "JSON-LD".

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。

Evaluate Agent Skill design quality against official specifications and best practices. Use when reviewing, auditing, or improving SKILL.md files and skill packages. Provides multi-dimensional scoring and actionable improvement suggestions.

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。

React useEffect best practices from official docs. Use when writing/reviewing useEffect, useState for derived values, data fetching, or state synchronization. Teaches when NOT to use Effect and better alternatives.

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 when creating a Claude Code slash command. Use when users ask to "create a command", "make a slash command", "add a command", or want to document a workflow as a reusable command. Essential for creating optimized, agent-executable slash commands with proper structure and best practices.

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 professional research posters in LaTeX using beamerposter, tikzposter, or baposter. Support for conference presentations, academic posters, and scientific communication. Includes layout design, color schemes, multi-column formats, figure integration, and poster-specific best practices for visual communication.

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 Parallel CLI for web search, URL extraction, deep research, structured data enrichment, entity discovery, and recurring web monitoring. Best for requests that explicitly need current web evidence, academic-source discovery, repeated entity lookups, exhaustive reports, or ongoing change tracking.

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。

Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.

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。

Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation". Use when the user mentions "pricing", "how much should we charge", "willingness to pay", "pricing page", "packaging", "freemium vs free trial", "are we leaving money on the table", "nobody buys at this price", "price increase", or "good-better-best". Also trigger when designing or auditing pricing and packaging, validating willingness to pay before building, segmenting customers by value, or choosing between subscription, usage-based, and freemium models. Covers price-before-product, willingness-to-pay talks, the four failures (feature shock, minivation, hidden gem, undead), leader/filler/killer packaging, and behavioral pricing. For offers and guarantees, see hundred-million-offers. For what customers value, see jobs-to-be-done.

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。

Apply meta-principles of software craftsmanship: DRY, orthogonality, tracer bullets, and design by contract. Use when the user mentions "best practices", "pragmatic approach", "broken windows", "tracer bullet", "software craftsmanship", "avoid technical debt", "code ownership", or "how do I become a better developer". Also trigger when evaluating build-vs-buy decisions, designing estimation approaches, or choosing between reversible and irreversible architectural decisions. Covers estimation, domain languages, and reversibility. For code-level quality, see clean-code. For refactoring techniques, see refactoring-patterns.

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。

Define product positioning by mapping competitive alternatives, unique attributes, and best-fit customers to the right market category. Use when the user mentions "positioning", "competitive alternatives", "how to position", "market category", "positioning canvas", "repositioning", "category creation", "what category are we in", or "why prospects dont get what we do". Also trigger when launching a new product, entering a crowded market, or diagnosing why prospects dont grasp the product's value. Covers the positioning canvas and team workshops. For customer jobs analysis, see jobs-to-be-done. For go-to-market, see crossing-the-chasm.

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。

Cut one long podcast, interview, course, livestream, or other source video into social-ready shorts, reels, highlights, or clip timelines from existing project media. Use when the user asks to cut a long video into Shorts, Reels, TikToks, Xiaohongshu posts, best moments, highlights, or multiple clips.

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。

Authors and structures professional-grade agent skills following the agentskills.io spec. Use when creating new skill directories, drafting procedural instructions, or optimizing metadata for discoverability. Don't use for general documentation, non-agentic library code, or README files.

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 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。

Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when creating components, pages, features, fetching data, styling, routing, or working with frontend code.

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。

When the user wants to get press coverage, media mentions, or editorial features for their app — including writing press releases, pitching journalists, getting on "best apps" lists, or building an app press kit. Use when the user mentions "press", "PR", "media coverage", "TechCrunch", "journalist", "press release", "app press kit", "get featured in media", "editorial coverage", "review from a blogger", or "app launch announcement". For Apple editorial featuring, see app-store-featured. For launch strategy, see app-launch.

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。

When the user wants to design, test, or optimize their app's paywall — layout, copy, pricing display, trial offers, plan structure, hard vs soft paywall, paywall placement, or paywall A/B tests. Use when the user mentions "paywall", "paywall design", "paywall conversion", "trial-to-paid", "soft paywall", "hard paywall", "paywall A/B test", "paywall copy", "plan picker", "annual vs monthly display", "best paywall", "RevenueCat paywall", "Superwall", "Adapty", or "my paywall isn't converting". For overall pricing strategy and monetization model choice, see monetization-strategy. For trial nurture, dunning, and churn, see subscription-lifecycle. For where in the onboarding the paywall fires, see onboarding-optimization.

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。

Standards and audits for writing academic papers, especially ML/NLP submissions to NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL. Covers the author's house prose rules (zero em dashes, zero fluff, every sentence earns its place), verification of hallucinated claims and hallucinated or malformed bibliography entries, the ACL policy on AI writing assistance and what must be disclosed, and best practices for paper structure, experiments, reproducibility checklists, and rebuttals. Use this skill whenever the user is drafting, editing, polishing, restructuring, or reviewing a paper, abstract, intro, related work, rebuttal, or camera-ready; whenever they ask to "clean up" or "tighten" academic writing; whenever citations or a .bib file need checking; and whenever they ask what has to be disclosed about AI assistance. Reach for it even when the user only says "make this section better", "check my references", or "is this ready to submit".

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。