「ai platform」の検索結果

Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.

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。

Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.

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。

Expert security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).

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, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance 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。

Mantém a documentação técnica viva no Notion e no repositório — arquitetura, runbooks, inventário, ADRs e procedimentos operacionais, gerados a partir da infraestrutura real. Use quando o usuário disser "documentar", "runbook", "ADR", "wiki", "Notion", "atualizar a documentação", "inventário", "ninguém sabe como isso funciona".

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。

Interactive developer experience plan review. Explores developer personas, benchmarks against competitors, designs magical moments, and traces friction points before scoring. Three modes: DX EXPANSION (competitive advantage), DX POLISH (bulletproof every touchpoint), DX TRIAGE (critical gaps only). Use when asked to "DX review", "developer experience audit", "devex review", or "API design review". Proactively suggest when the user has a plan for developer-facing products (APIs, CLIs, SDKs, libraries, platforms, docs). (gstack) Voice triggers (speech-to-text aliases): "dx review", "developer experience review", "devex review", "devex audit", "API design review", "onboarding 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。

Elite mobile app image-generation skill for creating premium, app-native screen concepts and flows. Designed for iOS, Android, and cross-platform mobile products. Prioritizes clean hierarchy, comfortably readable text, strong multi-screen consistency, controlled color palettes, non-generic creative direction, textured surfaces, image-led composition, tasteful custom iconography, and clean phone mockup framing. By default, screens should be shown inside a subtle premium iPhone or similar phone mockup with a visible frame, while the main focus stays on the app content itself. This skill generates images only. It does not write 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。

Write a rigorous, decision-grade experiment spec — falsifiable hypothesis, primary metric, guardrails, randomisation unit, exposure definition, method (A/B, holdout, switchback, quasi-experiment, MAB), MDE/duration plan, peek policy, validity threats, and pre-committed decision rule. Platform-agnostic. Load when the user has a candidate experiment and needs to spec it before launch, or says "spec this experiment", "write the test plan", "design this A/B test", "what's the hypothesis", "how big a sample do we need", "how long should we run this", "define the metrics for this test", or when the experimentation orchestrator routes 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。

Expert security auditor for AI Skills and Bundles. Performs non-intrusive static analysis to identify malicious patterns, data leaks, system stability risks, and obfuscated payloads across Windows, macOS, Linux/Unix, and Mobile (Android/iOS).

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。

Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.

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, iterate, and scale paid ad creative for Google Ads, Meta, LinkedIn, TikTok, and similar platforms. Use when generating headlines, descriptions, primary text, or large sets of ad variations for testing and performance 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。

Designs adaptive clinical trials including group-sequential (O'Brien-Fleming, Pocock, Lan-DeMets spending), sample-size re-estimation (blinded Friede-Kieser, unblinded Cui-Hung-Wang, Mehta-Pocock promising zone), seamless Phase 2/3 with treatment-arm selection, population enrichment, and response-adaptive randomisation. Covers FDA 2019 Final Adaptive Designs Guidance, FDA 2022 Master Protocols, and ICH E20 Step 2b/3 draft (June 2025, NOT final). Use when planning interim analyses, sample-size re-estimation, or master/platform-trial designs.

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 adding/changing a CMS surface manifest, the site_structure/html_pages_structure framing XML, a CMS context menu/extraSections wiring, or the cms-authoring platform skill. Also use when a new CMS route/tab needs an agent entry point.

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 whenever a form needs to accept ONE image and produce permanent public URLs for one or more platform-specific sizes (OG image, social posts, avatars, logos, favicons, app icons). Replaces every legacy image-URL input, single-size uploader, and base64-data-URL flow. Triggers when you see a manual `<input type="url">` for an image, a single-size uploader, or anywhere a `dataUrl` could leak into a clipboard or a saved record.

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。

The watch-fix-rerun method for making an existing platform agent or automated process efficient and correct: baseline its ledger, run one unit yourself, fix the class behind every wasted call, rerun, record. Use when asked to improve, optimize, watch, or 'make efficient' an agent, a sandbox session, a sync job, or any recurring automated process.

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。

Putting a platform feature on the Board (/board) as an Add-menu item with its real component and full agent surface. Use when adding a feature, record type or 'X on the board', or editing features/board/items/** or a tile body.

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。

The one association system (platform.associations) and schema-qualified table refs. Use when touching an M2M junction table, an associate_*/attach_*/tag_* RPC, FK columns used as tags, a 'things attached to X' list or card, or a PGRST205 / 42703 table-not-found on a bare .from().

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。

Platform agent skill and content blocks that teach agents a render block, building the block first if new. Use when asked to create the skill for a render block, skill-ify flashcards or quiz, add content blocks for a block, or add a new render block type. NOT for tool result displays (use create-tool-renderer).

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。

Locate CCSPlayer_WeaponServices::DropWeapon in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CCSPlayer_WeaponServices::DropWeapon" (symbol CCSPlayer_WeaponServices_DropWeapon). This is a VIRTUAL function — emit the vtable slot, NOT a byte signature. Resolve the CCSPlayer_WeaponServices vtable via RTTI and identify the DropWeapon slot: the body takes a CBasePlayerWeapon handle/pointer, detaches it from the player, spawns the dropped weapon entity and transfers ownership. Verify by xrefs from weapon-drop commands (!!drop) and pickup logic. vtable slots commonly differ between platforms — never assume identical indices. Trigger: CCSPlayer_WeaponServices_DropWeapon, CCSPlayer_WeaponServices::DropWeapon

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 and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries/mutations/actions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM/agent workflows on Convex's one-platform 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。

Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.

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。

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.

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Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.

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。

Scrape reviews, ratings, and brand mentions from multiple platforms using Apify 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。