「rop」の検索結果

Scalingo is a European (French) Platform-as-a-Service for deploying and operating web applications, background workers, and managed databases. Use this skill whenever the user mentions Scalingo, wants to deploy an app to Scalingo, work with the scalingo CLI, provision addons (PostgreSQL, MySQL, MongoDB, Redis, OpenSearch, InfluxDB), configure review apps, manage the scalingo.json manifest or a Procfile, scale containers, set up log drains, migrate from Heroku, use the Scalingo Terraform provider, or target sovereign regions (osc-fr1, osc-secnum-fr1 on SecNumCloud infrastructure). Also trigger for "deploy a French PaaS", "HDS-compliant hosting", "SecNumCloud deployment", or questions about Scalingo's Heroku-compatible buildpack model.

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。

Shared setup and rules for the report-skills bundle (report-publisher, client-reporter, proposal-tracker, deck-publisher, report-designer). Loaded by the individual skills for the common ReportRoom MCP publish flow, account bootstrap, and safety gates. Not invoked directly — pick the specific skill for the job.

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 you need to inspect NuGet package APIs, list public types, or decompile method/property signatures. Keywords: inspect package API, list types, decompile type, method signatures, NuGet interface.

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。

Check proposed stack, data flows, cloud choices, and delivery controls against declared enterprise policies, compliance frameworks, and security controls. Trigger at R2/R3 risk classification, before locking architecture decisions, or when the operating profile names a governance pointer.

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。

Measure, root-cause, fix, verify and record performance contention on a developer machine: cloud-sync daemons (iCloud Drive, OneDrive, Dropbox, Google Drive), file indexers, AI-tool MCP server fleets, and automation browsers left behind by tests and browser skills. Trigger when the machine is slow, apps freeze, browser or MCP tool calls time out, load exceeds the core count, or before and after any UI/UX/performance test run. Includes the L0–L4 optimisation scale and the test-hygiene contract.

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 revising or reviewing scientific, technical, or academic manuscripts, proposals, abstracts, reports, or related writing for precision, concision, logical cohesion, citation support, evidence alignment, and objective scholarly tone.

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。

Format and publish rich Notion documents with structured sections, code blocks, tables, callouts, quotes, mermaid diagrams, and emojis. Use when the user asks to organize, write, or save content to Notion (e.g., "notion에 정리해줘", "notion에 저장해줘"), or when invoked with /notion-format. Detects content type (tech-doc, meeting-notes, analysis, tutorial, bug-report) and applies the appropriate formatting template automatically.

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。

Shaping a UI component tree — composition vs inheritance, slot patterns, prop API design, controlled vs uncontrolled, polymorphic — on 'split this component'. Feeds react-shadcn-ui.

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 cross-workspace import will not resolve — cannot find module @org/*, TS2307 — to link the packages properly with the workspace: protocol instead of patching tsconfig paths.

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 balancing eng-team velocity vs quality vs burnout — on-call load, focus fragmentation, reorg shock. Triggers on 'team is burning out', 'why is velocity dropping'.

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 for deep React analysis: component tree, state flow, props flow, hooks usage, rendering behavior, and React-specific failure 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。

Use when the rule set is over the Augment budget, when a new rule would breach it, or when asked to audit / merge / prune rules — runs the audit pipeline and proposes a verdict per rule.

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 the user says 'create service', 'new service class', or needs a PHP service following SOLID principles with proper DI and repository usage.

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 shaping a Livewire component before code — full-page vs partial, parent/child split, event flow, state-vs-props boundary, hydration cost — even on 'add this Livewire component'.

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 customer onboarding — time-to-first-value, milestone design, friction audit, drop-off diagnosis. Triggers on 'fix onboarding', 'why do new accounts churn fast'.

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 character must stay visually identical across AI video scenes — locks identity tokens (silhouette, palette, wardrobe, prop) in JSON. Triggers 'character lock', 'same character'.

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 polling external AIs (OpenAI, Anthropic) outside the host session for a neutral second opinion on a roadmap, diff, prompt, or file set — or 'cross-check with another model'.

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。

Combine independent work from two or more selected agents into one decision-ready research report, design, or proposal. Preserve useful complementary findings, develop stronger combined options, and present material alternatives only when they exist. Use when multiple perspectives should improve the product without forcing consensus or staging disagreement.

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。

Domine Django 5.x com views assíncronas, DRF, Celery e Django Channels. Construa aplicações web escaláveis com arquitetura apropriada, testes e deployment.

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。

Extraia dados estruturados de respostas de LLM com validação Pydantic, tente novamente automaticamente extrações que falharem, analise JSON complexo com segurança de tipo e transmita resultados parciais com Instructor - biblioteca de saída estruturada testada em batalha

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。

Especialista em construir produtos que envolvem APIs de IA (OpenAI, Anthropic, etc.) em ferramentas focadas pela qual as pessoas pagarão. Não apenas 'ChatGPT mas diferente' - produtos que resolvem problemas específicos com IA. Cobre engenharia de prompts para produtos, gestão de custos, rate limiting e construção de negócios de IA defensáveis. Use quando: wrapper de IA, produto GPT, ferramenta IA, envolver IA, IA SaaS.

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。

Construa agentes de IA prontos para produção com PydanticAI — type-safe tool use, structured outputs, dependency injection, e suporte multi-modelo.

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。

Estratégias de cache para prompts de LLM incluindo cache de prompt da Anthropic, cache de resposta e CAG (Cache Augmented Generation) Use quando: prompt caching, cache prompt, response cache, cag, cache augmented.

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。

Modelo de reconhecimento de fala de propósito geral da OpenAI. Suporta 99 idiomas, transcrição, tradução para inglês e identificação de idioma. Seis tamanhos de modelo, de tiny (39M parâmetros) a large (1550M parâmetros). Use para speech-to-text, transcrição de podcasts ou processamento de áudio multilíngue. Melhor para ASR robusto e multilíngue.

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。