「library」の検索結果

Use Neo4j GenAI Plugin ai.text.* functions and procedures for in-Cypher embedding generation, text completion, structured output, chat, tokenization, and batch ingestion. Covers ai.text.embed(), ai.text.embedBatch(), ai.text.completion(), ai.text.structuredCompletion(), ai.text.aggregateCompletion(), ai.text.chat(), ai.text.tokenCount(), ai.text.chunkByTokenLimit(), and provider configuration for OpenAI, Azure OpenAI, VertexAI, and Amazon Bedrock. Requires CYPHER 25. Replaces deprecated genai.vector.encode(). Use when writing pure-Cypher GraphRAG, embedding nodes in-graph, generating structured maps from prompts, or calling LLMs inside Cypher queries. Does NOT handle neo4j-graphrag Python library pipelines — use neo4j-graphrag-skill. Does NOT handle vector index creation/search — use neo4j-vector-index-skill.

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Use when building a 3D web game with three.js, Babylon.js or PlayCanvas - render loop and delta per library, fixed-step physics with Rapier or Havok, explicit dispose of GPU resources, instancing and draw-call budgets, glTF with Draco/meshopt/KTX2, pixel ratio and resize, WebGPU opt-in, React Three Fiber notes, and headless testing.

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Use when the mobile repository has no theme tokens or component library yet (a new app, an "Apply design system" task, or a task that asks for one), before building any screen - writes the approved design system's generated files from get_design_system (files true) and builds the theme from them when there is one.

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Use on every UI change - Atomic Design levels, reuse-before-build, correct placement, and import direction through the shared component library.

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Use when the repository has no design system yet (no tokens, no component library - a new site/app, an "Apply design system" task, or a task that asks for one), before building any page section - writes the approved design system's generated files from get_design_system (files true) and builds the tokens on them when there is one.

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Use when Java is chosen but Quarkus does not fit - build the service with Spring Boot using the same clean layering, only when a required library lacks a Quarkus extension or the repo already standardizes on Spring

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Use when adding or reusing Flutter UI - organize widgets as atoms, molecules, and organisms in a shared library and never hand-roll a component that already exists

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Use when writing or changing any React component - React Testing Library tests are behavior-focused (byRole first), use user-event, assert on accessible output, one behavior per test, and run in npm test

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Generate unit, integration, E2E, and visual regression tests following the Testing Trophy methodology (80% integration). Covers Vitest/Jest, Testing Library, Playwright, MSW for API mocking, snapshot strategy, visual regression (Chromatic/Percy/Playwright), test factories with Faker, and CI sharding. Use when user asks to write tests, set up testing framework, mock API/dependencies, improve coverage, or add visual regression. Do NOT use for performance/load testing, production monitoring, or type testing (covered by TypeScript).

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This skill should be used when the user asks to "use bilibili API", "download bilibili video", "get bilibili user info", "list bilibili favorites", "send bilibili danmaku", "upload video to bilibili", "monitor bilibili live room", "search bilibili", "get bilibili comments", or needs guidance on the bilibili_api Python library usage, authentication, API endpoints, or workflow patterns.

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TypeScript/JavaScript conventions. Apply automatically whenever writing or editing JavaScript, TypeScript, JSX, or TSX code (.js/.jsx/.ts/.tsx) — functions, types, type safety, immutability, error handling, comments, file size, exports, naming, and library conventions for dates and data handling (ts-belt, ts-pattern). Use for any new code or refactor in these languages. For React-specific rules (components, hooks, JSX, TanStack Query, Zustand, React Hook Form), also apply the react skill.

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Use when creating, managing, or optimizing paid advertising campaigns across any platform. Covers ad copy generation, ad creative strategy, campaign management, and competitive intelligence. Triggers on: ad copy, ad creative, paid ads, paid advertising, Facebook ads, LinkedIn ads, Google ads, Meta ads, ad campaign, ad strategy, ad testing, competitive ads, competitor ads, ad library, ad analysis, ad creative generation, campaign management, ROAS, CPC, CTR. Use this skill whenever the user mentions ads, paid channels, ad campaigns, ad copy, ad performance, or wants to analyze competitor advertising.

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Audit and improve the accessibility of the timepicker-ui LIBRARY (app/src) - ARIA, keyboard operability, focus trap/management, screen-reader announcements, labels - against WCAG 2.2 AA and the WAI-ARIA Authoring Practices. Use when the user wants an a11y audit/fix of the picker itself (clock, wheel, plugins, modal, inputs). Drives the accessibility subagent in an audit → approve → apply flow. Does NOT cover docs-app (use /docs-a11y for that).

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Audit and improve the accessibility of the timepicker-ui documentation site (docs-app/) - landmarks, heading order, skip links, keyboard nav, focus management in the command menu / sidebar / dialogs, color contrast, alt text, ARIA on custom components, Radix usage, reduced motion - against WCAG 2.2 AA. Use when the user wants an a11y audit/fix of the docs site. Drives the docs-accessibility subagent in an audit → approve → apply flow. Does NOT cover the library (use /a11y for that).

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Any live-web task via the Firecrawl CLI — including ordinary web research: searching the web, reading or extracting pages, gathering sources, discovering site URLs, bulk extraction, downloading a site, change alerts, or pages needing clicks/login — web only; local files route to firecrawl-parse. For papers use firecrawl-research-index; for library, API, error, or bug questions use firecrawl-developer-index.

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Validates a UX spec, HUD design, or interaction pattern library for completeness, accessibility compliance, GDD alignment, and implementation readiness. Produces APPROVED / NEEDS REVISION / MAJOR REVISION NEEDED verdict with specific gaps.

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Guided, section-by-section authoring of the master architecture document for the game. Reads all GDDs, the systems index, existing ADRs, and the engine reference library to produce a complete architecture blueprint before any code is written. Engine-version-aware: flags knowledge gaps and validates decisions against the pinned engine version.

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Promote a validated pattern into a reusable Skill in AgentDB's skill library. Use when the same approach has worked 3+ times across episodes, or when the user explicitly says "make this a skill" / "save this as reusable".

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Filter Shopify standalone stores by multiple dimensions (store name/domain, country, years since creation, product count, ad count, monthly visits, monthly orders, social media followers, etc.). Triggered when users mention Shopify stores, Shopify store analysis, standalone stores, Shopify sellers, competitor standalone stores, Shopify monthly visits, standalone store ad library, shopify stores, or Shopify store query. Even if the user does not mention the tool name, this skill should be triggered whenever searching for stores, filtering store data, or analyzing store performance on Shopify standalone stores.

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Search Etsy category data by name, ID, or parent IDs to find category identifiers for product/store filtering. Trigger when user mentions Etsy category, Etsy category ID, Etsy category tree, Etsy category lookup, syncEtsyCategory, or category search — even if the tool name is not mentioned, as long as the need is to find a category ID by keyword in a locally synced Etsy category library.

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Code review focused exclusively on over-engineering. Finds what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. One line per finding: location, what to cut, what replaces it. Use when the user says "review for over-engineering", "what can we delete", "is this over-engineered", "simplify review", or invokes /ponytail-review. Complements correctness-focused review, this one only hunts complexity.

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Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", and whenever they complain about over-engineering, bloat, boilerplate, or unnecessary dependencies.

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When the user needs a comprehensive marketing plan for a client, a company they advise, or their own product. Also use when the user mentions "marketing plan," "growth plan," "GTM plan," "go-to-market plan," "AARRR plan," "90-day marketing plan," "12-month marketing roadmap," "fractional CMO plan," or "fCMO plan." Generates an exhaustive 13-section plan structured by AARRR (Acquisition, Activation, Retention, Referral, Revenue), customized to the client's current budget, team, and stage, mapped to future funding milestones, cross-referenced with the 139-idea marketing-ideas library and an embedded 17-section current-state audit rubric, with a full marketing operations stack showing which skills and MCP/API integrations execute each part. Outputs a Notion-paste-ready markdown document. For positioning and ICP context before planning, see product-marketing. For stage-specific deep work, see onboarding, signup, emails, referrals, pricing.

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Grounds every implementation decision in official documentation. Use when you want to verify an approach against the official docs before implementing it, or when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.

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。