「building」の検索結果

Generic civic intelligence aggregator for any US city — daily local digest of construction permits, crime, new businesses, public officials, legislation, elections, arrests, and local news, keyed off principal's Hometown. Writes JSON consumed by Pulse LOCAL tab. Crime delegates to a dedicated crime-stats skill. Workflows: DailyBrief, Construction, Crime, Business, Officials, Legislation, Elections, Arrests, News. USE WHEN local news, hometown news, council meeting, building permits, mayor, ballot measures, ordinance, recent arrests, civic intel, local digest. NOT FOR national news or arbitrary-city crime.

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。

Install and onboard a user into LifeOS — the Life Operating System (current state → ideal state via TELOS + the Algorithm). The agentic installer detects your OS + harness, wires hooks with permission, scaffolds your USER tree, pulls in sources you provide, and runs the TELOS / current→ideal interview that seeds your Pulse dashboard. USE WHEN install LifeOS, set up LifeOS, lifeos setup, lifeos-setup, lifeos interview, onboard me, run the interview, integrate LifeOS into my harness, update LifeOS, uninstall LifeOS, first-time setup, lifeos doctor, check my install, what capabilities are broken. NOT FOR building or cutting a LifeOS release (private release tooling), editing TELOS after onboarding (use Telos / Interview), or LifeOS system maintenance (use the private maintenance skill).

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。

Hardens LifeOS tests via property/mutation testing. USE WHEN harden, hardening, property test, property based testing, PBT, fast-check, mutation test, mutation testing, Stryker, CRAP score, CRAP analysis, DRY scan, jscpd, acceptance test mutation, strengthen tests, sharpen ISCs, find bugs example tests miss, universal quantified claim, shrink counterexample, what bugs am I missing, test the tests, test of the test. NOT FOR writing new feature tests (use bun test directly), grading agent output quality (use Evals), UI verification with real Chrome (use Interceptor), finding security vulnerabilities, or building new functionality.

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。

UI/UX design intelligence for web, mobile, and desktop. This skill should be used when designing, building, reviewing, or fixing interfaces, including pages, components, design systems, accessibility, interaction, responsive layout, typography, color, charts, and stack-specific UI implementation. Searchable local data: 79 searchable styles (50 active), 192 product palettes and reasoning profiles, 74 font pairings, 119 UX guidelines, 105 icons, 17 GSAP presets, 25 chart types, and 22 stacks.

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。

Export raw OpenTelemetry traces from an AI application to Confident AI's Observatory. TRIGGER when the user wants to send OpenTelemetry or OTLP traces/spans from an LLM app, agent, RAG pipeline, or chatbot to Confident AI; configure the Confident AI OTLP endpoint; set confident.span.* or confident.trace.* attributes; export AI-app traces without the deepeval Python package; wire an OTLPSpanExporter, OpenTelemetry Collector, or vendor-neutral OTel SDK to Confident AI; or pick the US vs EU OTLP endpoint. Language-agnostic: the mechanism is OTLP attribute keys plus an exporter endpoint. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill); for instrumenting with the DeepEval SDK's @observe decorator or framework integrations (use the `deepeval-tracing` skill); or for non-AI software such as web servers, CRUD backends, or infrastructure: the confident.* attributes describe AI components only.

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。

Instrument an AI application with DeepEval's native tracing so its behavior is visible in Confident AI. TRIGGER when the user wants to add DeepEval tracing or @observe to an LLM app, agent, RAG pipeline, or chatbot; wire a framework, model-provider, or vector-database integration (LangGraph, LangChain, OpenAI Agents, LlamaIndex, Pydantic AI, CrewAI, and others); choose between a native integration and manual instrumentation; set span types, tags, or metadata; or send DeepEval-SDK traces to Confident AI's Observatory. DO NOT TRIGGER for building DeepEval pytest eval suites, datasets, goldens, metrics, or deepeval test run (use the `deepeval` skill), or for raw OpenTelemetry / OTLP export without the deepeval package (use the `deepeval-otel` skill). This skill is purely DeepEval-SDK instrumentation — producing well-formed traces, not running evals.

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 Three Fiber 3D renderer for json-render. Use when working with @json-render/react-three-fiber, building 3D scenes from JSON specs, rendering meshes/lights/models/environments, or integrating Three.js with json-render catalogs.

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 package for defining schemas, catalogs, and AI prompt generation for json-render. Use when working with @json-render/core, defining schemas, creating catalogs, or building JSON specs for UI/video generation.

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。

MCP Apps integration for json-render. Use when building MCP servers that render interactive UIs in Claude, ChatGPT, Cursor, or VS Code, or when integrating json-render with the Model Context Protocol.

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。

Svelte 5 renderer for json-render that turns JSON specs into Svelte component trees. Use when working with @json-render/svelte, building Svelte UIs from JSON, creating component catalogs, or rendering AI-generated specs.

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。

Vue 3 renderer for json-render. Use when building Vue UIs from JSON specs, working with @json-render/vue, defining Vue component registries, or rendering AI-generated specs in Vue.

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。

Pre-built shadcn-svelte components for json-render Svelte apps. Use when working with @json-render/shadcn-svelte, adding standard UI components to a Svelte catalog, or building Svelte web UIs with shadcn-svelte + Tailwind CSS components.

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。

Remotion renderer for json-render that turns JSON timeline specs into videos. Use when working with @json-render/remotion, building video compositions from JSON, creating video catalogs, or rendering AI-generated video timelines.

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 Native renderer for json-render that turns JSON specs into native mobile UIs. Use when working with @json-render/react-native, building React Native UIs from JSON, creating mobile component catalogs, or rendering AI-generated specs on mobile.

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。

Next.js renderer for json-render that turns JSON specs into full Next.js applications with routes, layouts, SSR, and metadata. Use when working with @json-render/next, building Next.js apps from JSON specs, or creating AI-generated multi-page applications.

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。

Code generation utilities for json-render. Use when generating code from UI specs, building custom code exporters, traversing specs, or serializing props for @json-render/codegen.

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 renderer for json-render that turns JSON specs into React components. Use when working with @json-render/react, building React UIs from JSON, creating component catalogs, or rendering AI-generated specs.

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。

Pre-built shadcn/ui components for json-render. Use when working with @json-render/shadcn, adding standard UI components to a catalog, or building web UIs with Radix UI + Tailwind CSS components.

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。

Ink terminal renderer for json-render that turns JSON specs into interactive terminal UIs. Use when working with @json-render/ink, building terminal UIs from JSON, creating terminal component catalogs, or rendering AI-generated specs in the terminal.

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。

SolidJS renderer for json-render. Use when building @json-render/solid catalogs/registries, wiring Renderer providers, implementing bindings/actions, or troubleshooting Solid-specific reactivity 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。

React Email renderer for json-render that turns JSON specs into HTML or plain-text emails using @react-email/components and @react-email/render. Use when working with @json-render/react-email, building transactional or marketing emails from JSON, creating email catalogs, rendering AI-generated email specs, or when the user mentions react-email, HTML email, or transactional email.

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。

A comprehensive collection of Agent Skills for context engineering, harness engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, evaluating, or debugging agent systems that require effective context management and reliable operating loops.

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 building agent evaluation systems: deterministic checks, regression suites, multi-dimensional rubrics, quality gates, production monitoring, baseline comparison, and outcome measurement for agent pipelines.

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。

Complete Foundry PoC writing guide + all cheatcodes + DeFiHackLabs reproduction patterns. Use this when building a proof of concept exploit, setting up a fork test, using Foundry cheatcodes, or reproducing a known DeFi hack for learning.

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。