Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI, Anthropic, and Google APIs.
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。
9,048 件 ・ 関連度順
概要と使いどころ
Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI, Anthropic, and Google APIs.
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 a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
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 in Drizzle ORM for TypeScript — schema design, relational queries, migrations, and serverless database integration. Use when building type-safe database layers with Drizzle.
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。
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
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 rigorous, conversion-focused marketing copy for landing pages and emails. Enforces brief confirmation and strict no-fabrication rules.
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。
Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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 a task needs a small, throwaway multi-agent fan-out (a couple of parallel workers plus a review pass) in ANY project — trigger phrases "spawn a few parallel agents", "fan out", "quick worker team" — without the full /startcycle-graph contract, no .agents/graph.md bootstrap, no state.json schema, no persistent files. Roles run on the session model unless `.aos/pipeline.json` overrides one (an external CLI can take the worker step) and portable across machines that may not have Antigravity/OpenCode/Codex installed.
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 designing electrical schematics, PCB layouts, KiCad projects, or OpenSCAD enclosures — trace geometry, impedance, stackup, DFM/DRC/ERC sign-off, and hardware-software co-design boundaries.
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。
BDB Engineering Godmode, enforcing strict Domain-Driven Design, TypeScript strictness, and Clean Architecture. Use when implementing backend/fullstack features or running the systematic 5-step debugging triage.
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。
阿里云 AnalyticDB (ADB) for MySQL 只读数据分析。 多维分析(计数/聚合/时间序列)、交叉验证、Schema 文档生成、多 Profile。
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。
Core Swift development workflows for Xcode and Swift tooling, including project setup, dependency management, concurrency guidance, language/runtime best practices, and troubleshooting build or package resolution issues. Use when working on Swift tasks across a codebase, especially package/tooling/runtime work and cross-cutting Swift conventions (mutation semantics, naming, enum/file rules, import hygiene), including in SwiftUI projects.
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。
Audit macOS AppKit interfaces for accessibility, focusing on VoiceOver, keyboard navigation, and semantics
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。
iOS design system tokens for Pencil MCP: SF Pro typography scale, iOS semantic colors (light + dark mode hex values), spacing grid, touch targets, corner radii, and component heights. Use when initializing a .pen file for iOS design or setting up design variables.
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。
iOS-specific Pencil MCP design workflow. Creates iOS screens on canvas following Apple HIG with proper SF Pro typography, semantic colors, and 8pt spacing grid. Use when designing iOS UI in .pen files. Requires Pencil MCP server.
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。
Implement Swift Codable models for JSON and property-list encoding and decoding with JSONDecoder, JSONEncoder, CodingKeys, and custom init(from:) or encode(to:). Use when parsing API responses, remapping keys, flattening nested JSON, handling date or data decoding strategies, decoding heterogeneous arrays, or integrating Codable with URLSession, SwiftData, or UserDefaults.
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。
Diagnose, fix, or validate SwiftUI animation and scroll behavior by temporarily instrumenting views with MotionEyes, capturing console traces over time, and comparing motion data to user intent or test expectations. Use when users report bugs such as wrong direction, premature fade, timing or easing mismatch, unexpected movement, missing movement, incorrect relative movement between views, scroll jumps, scroll restoration drift, content-offset desynchronization, or when they want to turn MotionEyes traces into focused assertions. Prefer XcodeBuildMCP log capture first and fallback to CLI log streaming; remove only agent-added MotionEyes instrumentation after validation.
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。
Implement App Intents for Siri, Shortcuts, Spotlight, widgets, Control Center, and Apple Intelligence on iOS. Covers AppIntent actions, AppEntity and EntityQuery models, AppShortcutsProvider phrases, IndexedEntity Spotlight indexing, WidgetConfigurationIntent, SnippetIntent, and assistant schemas. Use when exposing app actions or entities to system surfaces.
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。
Integrate on-device AI using Foundation Models framework, Core ML, and open-source LLM runtimes on Apple Silicon. Covers Foundation Models (LanguageModelSession, @Generable, @Guide, SystemLanguageModel, structured output, tool calling), Core ML (coremltools, model conversion, quantization, palettization, pruning, Neural Engine, MLTensor), MLX Swift (transformer inference, unified memory), and llama.cpp (GGUF, cross-platform LLM). Use when building tool-calling AI features, working with guided generation schemas, converting models, or running on-device inference.
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。
21 production-ready scripts for iOS app testing, building, and automation. Provides semantic UI navigation, build automation, accessibility testing, and simulator lifecycle management. Optimized for AI agents with minimal token 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。
Use when someone asks to write, rewrite, review, or improve text that appears inside a product or interface. Examples: "review the UX copy", "is there a better way to phrase this", "rewrite this error message", "write copy for this screen/flow/page", reviewing button labels, improving CLI output messages, writing onboarding copy, settings descriptions, or confirmation dialogs. Trigger whenever the request involves wording shown to end users inside software — apps, web, CLI, email notifications, modals, tooltips, empty states, or alerts. Also trigger for vague requests like "review the UX" where interface copy review is implied. Do NOT trigger for content marketing, blog posts, app store listings, API docs, brand guides, cover letters, or interview questions — this is a technical writing skill for interface language.
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。
Strips AI fingerprints from written text by enforcing banned vocabulary, forbidden sentence structures, and authentic prose patterns. Use when writing articles, documentation, social content, emails, or any text that should read as human-authored rather than AI-generated.
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。
Helps detection engineers identify coverage blind spots in system command execution detection rules, evaluate bypass risks, and reduce false negatives. Strictly limited to system command execution rules; not applicable to browser credential theft or abnormal process creation without command semantics.
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 the user asks how to "use VibeTags", "add VibeTags annotations", "set up AI guardrails", "protect code from AI", "configure AI platforms", asks about @AILocked, @AIContext, @AIDraft, @AIAudit, @AIIgnore, @AIPrivacy, @AICore, @AIPerformance, @AIContract, @AITestDriven, @AIThreadSafe, @AIImmutable, @AIDeprecated, @AIObservability, @AIRegulation, @AIArchitecture, @AILegacyBridge, @AIStrictClasspath, @AIInternationalized, @AIPublicAPI, @AISchemaSafe, @AIStrictExceptions, @AIStrictTypes, @AIParallelTests, @AIIdempotent, @AIFeatureFlag, @AISecure, @AICallersOnly, @AISandboxOnly, @AIMemoryBudget, @AIPure, @AIDomainModel, @AIExtensible, @AIInputSanitized, @AISecureLogging, @AIExplain, @AIPrototype, @AISunset, @AITemporary annotations, or wants to control how AI tools interact with Java 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。
Create a company-specific job application package from a JD, resume.md, cover letter drafts, HR review, and optional company values input. Use when the user wants 지원 패키지, submission checklist, application folder structure, final answer snippets, email draft support, or safe pre-submission preparation without automatic final submission.
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。