「engine」の検索結果

Use when the user asks for Superloopy clone or asks to clone, rebuild, reverse-engineer, replicate, or copy a website or page into a Superloopy-governed implementation. Triggers on "loopy clone", target URLs plus requests such as "clone this site", "rebuild this page", "make a copy of this website", "pixel-perfect clone", or "AI website clone". Requires browser automation and records component specs, assets, implementation, build output, and visual QA as Superloopy evidence.

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。

Review employee reimbursement requests against the company's sample expense policy and draft submission notes.

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。

Turn one idea into platform-native content for X, LinkedIn, TikTok, YouTube, newsletters. Use when the user wants social posts, threads, scripts, or content calendars.

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。

Comprehensive sales and revenue operations skill. Use when building a sales team, doing founder-led sales, hiring first sales reps, navigating enterprise deals, implementing product-led sales, designing sales compensation plans, defining ICP, mapping buyer personas, or optimizing the revenue engine (RevOps). Activates for: sales strategy, rev ops, revenue operations, sales enablement, sales compensation, ICP, ideal customer profile, buyer persona, sales process, deal execution, lead scoring, lead routing, lead lifecycle, MQL, SQL, pipeline management, CRM automation, sales qualification, BANT, MEDDIC, founder sales, enterprise sales, product-led sales, startup sales, SDR, AE, quota, ramp, commission plan.

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。

Growth strategy for product-led and loop-driven growth systems. Use when building growth strategy, designing growth loops, planning acquisition channels, evaluating network effects, deciding when to scale, or coordinating product, engineering, data, and marketing around growth. For SEO audits use seo-and-aeo-strategy; for page/form CRO use conversion-rate-optimization; for A/B test design use ab-test-setup.

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。

Unified image-generation engine for the product-shots ecosystem. Dispatches to the right model family (OpenAI gpt-image-2 / Gemini gemini-3-pro-image-preview Nano Banana Pro) with one parameterised script for text-to-image and image-to-image. Primary backend: OmniMaaS / Cloubic gateway (https://api.omnimaas.com/v1); also supports any OpenAI-SDK-compatible gateway via fallback env vars. Auto-resizes oversized reference images to prevent edge-proxy timeouts. Use when the user says "generate an image", "make a picture", "create a visual", "render this", "edit this image", "做一张图", "生成图片", "改这张图" — or when invoked as the image-generation backend by another product-shots skill (main-image / detail-page / ad-creative / social-post / multi-angle). NOT a creative-direction skill: takes a prompt + optional reference images, returns a file path.

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。

Coverage-design method for qa-engineer — pyramid ratios per archetype, equivalence/boundary/property case selection, mutation score as the real coverage signal, and a flake-quarantine policy. Turns "coverage is 90%" (a number with no method) into a defensible test plan. Emits TEST-STRATEGY-{slug}.md, which the QA gate checks exists.

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。

Email/SMS lifecycle and deliverability framework for SMB Product-Builder products that send transactional or lifecycle messages (booking reminders, CRM sequences, receipts, win-back). Codifies provider selection (Resend/Postmark/Twilio/SendGrid), domain auth (SPF/DKIM/DMARC), consent and compliance (TCPA, CAN-SPAM, CASL, quiet hours, double opt-in), suppression-list discipline, and the transactional-vs-marketing split. Applied by integrations-engineer and senior-dev whenever a feature sends messages — so deliverability and consent are designed in, not bolted on after the first spam complaint.

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。

Onboarding-and-switching playbook for SMB Product-Builder products. Defines the first-run experience that turns a prospect leaving an incumbent (ServiceTitan/Toast/Mindbody/Shopify/QuickBooks) into an activated user — import-first onboarding, the activation milestone, sample-data fallback, and the time-to-first-value target. Applied by migration-import-engineer and architect/pm so onboarding is designed as a funnel, not an afterthought. Our whole wedge is "low switching cost"; this skill makes that real on day one.

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 pinned default technology stack for SMB Product-Builder products. One source of truth so the architect, app-scaffolder, auth-engineer, and senior-dev never re-decide the stack per build — they build ON it. Covers framework, ORM/DB, auth, UI, payments/email/SMS, files, jobs, testing, hosting, and observability, with the chosen default + the one sanctioned alternative for each. Applied whenever a new product is scaffolded or a stack choice would otherwise be improvised. Re-deciding the stack every build is the biggest silent time sink; this kills it.

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。

通过鲲鹏投流工具完成账户检查、计划创建、关键词建议、素材选择、数据读取与复盘。

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 validate texture-state transitions for Blender animations without ugly whole-image crossfades, texture popping, misregistered morphs, or target-engine-incompatible Python-only swaps. Use when animating between multiple source textures, mascot/logo states, style states, lightmaps, decals, or UI skins.

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 Blender scenes to glTF/GLB (web/AR), FBX (game engines), OBJ (universal), USD (VFX pipelines), STL (3D printing). Includes Unreal collision hulls and Multires normal-map baking for low-poly export, per-format settings, embed/unpack textures, axis conversion, polygon optimization (Decimate), and target-platform validation. Use whenever the user asks to "export this", "save as glTF / FBX / OBJ / STL / USD", "package for Unity / Unreal / Three.js / web / AR / 3D print", or any output format conversion. Make sure to use this skill even if the user does not say "export" — also covers "package this for the web", "make it work in Unity", "send to Unreal", "save for 3D printing".

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。

Render Blender scenes with the right engine and settings — Cycles for photoreal, EEVEE for speed/stylized, sample counts, denoising (OptiX/OIDN), light path tuning, color management (AgX/Filmic), file output (PNG/EXR/MP4), animation rendering. Use whenever the user asks to "render this", "produce an image", "render a frame / animation", "make a final image", "save the render", or any output-generation request. Make sure to use this skill even if the user does not say "render" — also covers "make a picture", "save the result", "produce a final image", "export as image".

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 product and site search for end users. Use when choosing search engines, indexing, reindexing, relevance tuning, facets, autocomplete, merchandising, or search analytics.

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 transactional email systems and send infrastructure. Use when implementing resets, receipts, deliverability controls, templates, or inbound email 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。

Analyzes hazards in systems or AI agents: STPA, guardrails, safety cases, incident analysis. Use when an agent can take actions or send payments.

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 DevOps and platform engineering systems. Use when planning Kubernetes, Terraform, GitOps, CI/CD, observability, incident response, or cloud-native operations.

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。

Context-driven AI development with AGENTS.md, repo knowledge bases, Claude Code, Codex, and Copilot. Use when adopting repo-native AI workflows or multi-repo setups.

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。

Scores team or opt-in individual contribution quality from commit and PR history. Use when building engineering scorecards or coaching; for AI impact use dev-ai-coding-metrics.

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 lakehouse platforms across Iceberg, Delta, Hudi, and Paimon. Use when choosing catalogs, CDC paths, query engines, governance, or cost controls.

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。

Creates reusable vector-brain implementations: repo, docs, compliance. Use when building pgvector SQL, manifests, ingest scripts. Not for context design (dev-context-engineering).

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 cross-session agent memory: point-in-time facts, consolidation, tenant isolation. Use when auditing user memory or Mem0/Zep. Not for repo context (dev-context-engineering).

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。

AI knowledge engine - a memory system in 6 lines of code. remember/recall/forget/improve loop, vector + graph search, OpenClaw plugin supported.

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。