「zero」の検索結果

Symfony UX LiveComponent for reactive server-rendered UI -- components that re-render via AJAX on user interaction, zero JavaScript required. Use when building live search, real-time filtering, dynamic forms, inline validation, dependent selects, auto-save, polling, deferred/lazy rendering, or any UI that updates itself based on user input. Code triggers: AsLiveComponent, LiveProp, LiveAction, data-model, data-loading, data-live-action-url, ComponentWithFormTrait, LiveListener, emit, defer, lazy, polling. Also trigger when the user asks "how to build a search that filters as I type", "how to validate a form in real-time", "how to make a reactive component in PHP", "how to build dependent selects", "how to defer component rendering", "how to communicate between components via emit", "how to bind a form to a LiveComponent". Do NOT trigger for static reusable UI without reactivity (use twig-component), pure client-side JS behavior (use stimulus), or page-level navigation (use turbo).

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Hotwire Turbo for Symfony UX -- SPA-like speed with zero JavaScript. Covers Drive (navigation), Frames (partial page sections), and Streams (multi-target updates). Use when building ajax navigation, lazy-loaded sections, inline editing, pagination without reload, modals from the server, flash messages via streams, or real-time updates via Mercure/SSE. Code triggers: turbo-frame, turbo-stream, data-turbo-frame, data-turbo, data-turbo-action, turbo-stream-source, TurboStreamResponse, <twig:Turbo:Frame>, <twig:Turbo:Stream:Append>, <twig:Turbo:Stream:Replace>, turbo:before-fetch-request. Also trigger when the user asks "how to update part of the page without reload", "how to make navigation feel like SPA", "how to lazy-load a section", "how to do inline editing", "how to push real-time updates from server", "how to use Mercure with Turbo". Do NOT trigger for client-side JS behavior (use stimulus), server-rendered reactive components (use live-component), or reusable static UI (use twig-component).

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Stimulus JS framework for Symfony UX -- client-side behavior via HTML data attributes, zero server round-trips. Use when creating controllers for DOM manipulation, handling click/input/submit events, managing targets and values, wiring outlets between controllers, wrapping third-party JS libraries, or building toggles, dropdowns, modals, tabs, clipboard interactions. Code triggers: data-controller, data-action, data-target, data-*-value, data-*-class, data-*-outlet, stimulusFetch lazy, connect(), disconnect(), static targets, static values. Also trigger when the user asks "how do I add a click handler", "how to toggle a class", "how to build a dropdown/modal/tabs", "how to wrap a JS library in Symfony", "add keyboard shortcuts", "lazy-load a controller", "listen to global events", "communicate between controllers". Do NOT trigger for partial page updates without JS (use turbo), server-rendered reactivity (use live-component), or reusable Twig templates (use twig-component).

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Symfony UX Map for interactive maps with Leaflet or Google Maps in Symfony. Covers markers, polygons, polylines, circles, info windows, and LiveComponent integration. Use when displaying maps, placing markers, drawing shapes or routes, handling map events, building store locators, using custom tile layers, or making maps reactive with LiveComponent. Code triggers: <twig:ux:map />, Map(), Point(), Marker(), Polygon(), Polyline(), Circle(), InfoWindow(), MapOptionsInterface, ComponentWithMapTrait, fitBoundsToMarkers, ux:map:marker:before-create, ux:map:connect, SYMFONY_UX_MAP_DSN. Also trigger when the user asks "how to display a map", "how to add markers", "how to draw a polygon on a map", "how to handle map click events", "how to make a reactive map", "how to use Leaflet in Symfony", "how to use Google Maps in Symfony", "map not showing", "map has zero height". Do NOT trigger for SVG icons (use ux-icons) or general frontend interactivity (use stimulus).

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Turn a rough idea, a bug, or a batch of unsolved problems into well-structured GitHub issue(s) and file them with `gh`, auto-classifying type + labels from the content (recommend, then confirm) and following Rove's conventions (beginner-friendly framing, concrete file pointers, an acceptance checklist, zero AI/Anthropic attribution). Handles single, batch, and "file the unsolved problems" modes. Use when the user says "file an issue", "open a GitHub issue", "draft a good first issue", "batch these as issues", "上报 issue", "提个 issue", "报个 bug", "把没解决的发上去", or wants to hand low-priority tasks to outside contributors. Distinct from the daemon-owned internal issue store (`rove api issue-*`); this skill is for outward-facing GitHub issues.

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Dokploy is an open-source, self-hosted platform (an alternative to Heroku, Vercel and Netlify) that deploys applications, Docker Compose stacks and databases on your own server with Docker Swarm and Traefik, a web dashboard, automatic Let's Encrypt certificates and an HTTP API. Use when a user asks to "install Dokploy on a VPS", "deploy an app with Dokploy", "deploy a docker-compose project to Dokploy", "add a domain with HTTPS", "trigger a Dokploy deployment from CI", "create a Postgres database in Dokploy" or "set up zero-downtime deploys".

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DuckDB is an in-process analytical database that runs embedded inside your application with zero external dependencies. It can query CSV, Parquet, and JSON files directly without loading them into tables first, making it ideal for local data exploration, ETL pipelines, and analytical workloads where spinning up a server is overkill.

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You are an expert in Drizzle ORM, the lightweight TypeScript ORM that maps directly to SQL. You help developers write type-safe database queries that look like SQL (not a new query language), generate migrations from schema changes, and deploy to serverless environments with zero overhead — supporting Postgres, MySQL, SQLite, Turso, Neon, PlanetScale, and Cloudflare D1.

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Dokku is an open-source, single-server platform-as-a-service: it builds an app from a git push (buildpacks or a Dockerfile), runs it in Docker containers behind nginx, and manages domains, TLS, config and datastores through one CLI. Use when a user asks to "self-host a Heroku alternative", "set up git push deploys on a VPS", "deploy my app with Dokku", "add Postgres or Redis to a Dokku app", "get Let's Encrypt on Dokku", or "fix ports for a Dockerfile app on Dokku". Covers installation from the apt repository, deploys, environment variables, plugins, zero-downtime checks, storage and the k3s scheduler.

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You are an expert in Deno Deploy, the globally distributed serverless platform by Deno. You help developers deploy TypeScript/JavaScript applications to 35+ edge locations with zero cold starts, built-in KV storage, BroadcastChannel for real-time, cron scheduling, and npm compatibility — running code within milliseconds of users worldwide without managing infrastructure.

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You are an expert in Cloudflare Workers AI, the serverless AI inference platform running on Cloudflare's global network. You help developers run LLMs, embedding models, image generation, speech-to-text, and translation models at the edge with zero cold starts, pay-per-use pricing, and integration with Workers, Pages, and Vectorize — enabling AI features without managing GPU infrastructure.

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You are an expert in Biome, the Rust-based toolchain that replaces ESLint and Prettier with a single, fast tool. You help developers configure linting, formatting, and import sorting for JavaScript, TypeScript, JSX, JSON, and CSS — achieving 100x faster execution than ESLint+Prettier with zero configuration, unified diagnostics, and IDE integration.

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Assists with building content-driven websites using Astro's island architecture. Use when creating static sites, blogs, documentation, or marketing pages that ship zero JavaScript by default. Trigger words: astro, static site, island architecture, content collections, SSG, hybrid rendering, astro components.

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You are an expert in AWS Lambda, Amazon's serverless compute service. You help developers build event-driven applications using Lambda functions triggered by API Gateway, S3 events, SQS queues, DynamoDB streams, and scheduled events — with support for Node.js, Python, Go, Rust, Java, and container images, automatic scaling from zero to thousands of concurrent executions, and pay-per-invocation pricing.

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Expert guidance for Apache Arrow, the cross-language columnar memory format for analytics workloads. Helps developers use Arrow for high-performance data interchange between systems, zero-copy reads, and efficient columnar processing in Python (PyArrow) and JavaScript (Arrow JS).

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Warren Buffett said he looks for "economic castles protected by unbreachable moats." A moat is a sustainable competitive advantage that protects your business from competitors. Without a moat, success attracts competition that erodes your margins to zero. This skill covers identifying, building, and deepening moats. Network effects, switching costs, brand, scale economies, and the rarer moats like regulatory capture and counter-positioning. Use when "moat, defensibility, competitive advantage, network effects, switching costs, barrier to entry, unfair advantage, protect from competition, sustainable advantage, winner take all, flywheel, lock-in, moat, defensibility, strategy, network-effects, switching-costs, competitive-advantage, seven-powers" mentioned.

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Patterns for running AI models locally in browsers using WebGPU, Transformers.js, WebLLM, and ONNX Runtime. Zero API costs, full privacy. Use when "on-device AI, browser AI, WebLLM, Transformers.js, WebGPU, edge inference, offline AI, client-side ML, ONNX web, " mentioned.

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Use when training models across multiple GPUs or nodes, handling large models that don't fit in memory, or optimizing training throughput - covers DDP, FSDP, DeepSpeed ZeRO, model/data parallelism, and gradient checkpointingUse when ", " mentioned.

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Calculate, track, and report greenhouse gas emissions following GHG Protocol standards, including Scope 1, 2, and 3 emissions and science-based targets. Use when "carbon accounting, GHG emissions, scope 1, scope 2, scope 3, carbon footprint, emission factor, science-based target, SBTi, net zero, " mentioned.

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Don't die. Runway calculation, default alive vs. default dead, when to raise vs. cut, zero-based budgeting for startups. The math that keeps companies alive long enough to win. Burn rate is not just accounting - it's strategic leverage. Companies with runway have options. Companies without runway have desperation. Use when "burn rate, runway, default alive, default dead, how much money, when to raise, cutting costs, layoffs, cash management, should we hire, running out of money, bridge round, extend runway, ramen profitable, finance, runway, cash, burn, survival, fundraising, startup" mentioned.

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Mastery of the new frontier: AI-generated video that rivals—and reimagines—traditional production. This skill covers Veo3, Runway Gen-3, Sora, Kling, Pika, Luma Dream Machine, and the rapidly evolving landscape of neural video synthesis. We're not just using AI to replace traditional video—we're unlocking visuals that were previously impossible, unaffordable, or unimaginable. Flying through abstract data visualizations, impossible camera moves, photorealistic product renders from text, and consistent character performances without actors or sets. The practitioners of this skill understand that AI video is not about cost savings— it's about creative expansion. The ceiling has been removed. What would you create if production cost was zero and physics was optional? Use when "AI video, generate video, Veo3, Veo 3, Runway, Sora, Kling, Pika, Luma, text to video, image to video, video generation, AI footage, neural video, synthetic video, impossible shot, ai-video, veo3, runway, sora, kling, pika, generation, text-to-video, neural, synthesis" mentioned.

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Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragmented with inconsistent terminology. We use the CoALA cognitive architecture framework: semantic memory (facts), episodic memory (experiences), and procedural memory (how-to knowledge). Use when "agent memory, long-term memory, memory systems, remember across sessions, memory retrieval, episodic memory, semantic memory, vector store, rag, langmem, memgpt, conversation history, memory, vector-store, rag, retrieval, embedding, episodic, semantic, procedural, langmem, memgpt, pinecone, qdrant, chromadb" mentioned.

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Synthesize the single strongest EVIDENCE-BOUND reviewer case to reject a paper, built ONLY from the evidence ledger (claims.json) + the other auditors' confirmed findings — never free-floating LLM critique. Two fresh cross-model codex threads: an attack writes the ~200-word rejection paragraph (every accusation tagged to an existing claim_id/finding_id), a defense decomposes it and rules each point against the anchored evidence. MEMO-ONLY: emits adversarial-case-builder.memo.md (fed to the adjudicator via --memo) and carries NO verdict weight — tools/adjudicate_findings.py lists it in ZERO_WEIGHT_SKILLS and caps it at info. Honest-null allowed (the paper may survive). Run LAST. Detect-only. Adapted from ARIS kill-argument. Triggers: "adversarial case", "strongest objection", "rejection memo", "kill argument", "最强拒稿点".

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MEMO-ONLY prior-work overlap advisory: surfaces the two ADVISORY taxonomy signals neither a tool nor a model can decide from the paper alone — ADV-TRIVIAL-COMBINATION (standard A+B+C / 缝合 stapling) and ADV-DUPLICATE-PUBLICATION (repackaged / duplicate submission). The executor RETRIEVES candidate prior work (DBLP fuzzy-title + boolean · WebSearch · WebFetch) from the paper's own title + contribution spans in the evidence ledger; TWO fresh cross-model codex reviewers (one per axis) LAY OUT the overlap side-by-side against each anchored contribution claim. It NEVER rules 'trivial' or 'duplicate' (that is a human judgment) and absence of a match is NOT evidence of originality. Emits novelty-duplication-advisory.memo.md + an info-only findings mirror; carries NO verdict weight — tools/adjudicate_findings.py lists it in ZERO_WEIGHT_SKILLS and caps it at info. Detect-only. Adapted from ARIS novelty-check, reframed from 'is MY idea novel' to 'here is the overlap a reviewer should weigh'. Triggers: "novelty advisory", "duplication check", "prior-work overlap", "is this stapling", "缝合", "查重", "重复发表", "duplicate 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。