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概要と使いどころ
Avalia LLMs em mais de 60 benchmarks acadêmicos (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use quando benchmarking de qualidade de modelo, comparação de modelos, relatório de resultados acadêmicos ou rastreamento de progresso de treinamento. Padrão da indústria usado por EleutherAI, HuggingFace e laboratórios principais. Suporta HuggingFace, vLLM, 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。
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.
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。
Load this skill when configuring or reviewing CI/CD pipelines, GitHub Actions workflows, or automated testing setups. Ensures accessibility regressions are caught before code reaches production by enforcing quality gates, structured reporting, and layered automated + manual testing across all pages and user preferences.
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 Quality] Use when you need to combine /why-review + /fix in a recursive loop — each round runs /why-review to find validated findings then /fix to resolve them, then loops again over the CHANGED target until a fresh full /why-review produces zero findings (nothing left to fix).
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 Quality] Use to validate a spec artifact's decisions with the user across three contexts — a freshly-authored Feature Spec (idea-to-spec), an existing canonical spec before PBI decomposition (spec-to-pbi), or a refined idea + §8 test-specs (idea-to-pbi deep mode). Detects the context, walks every applicable validation category, and runs an exhaustive but budget-bounded blocking clarification gate so every non-obvious or conflicting decision is confirmed before the artifact drives downstream work.
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 Quality] Use when reviewing service-layer and API changes for production readiness.
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 Quality] Use when you need an AI-assisted Dev BA PIC review of PBI drafts.
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[Code Quality] Use when the user asks to analyze package upgrades, check for outdated dependencies, plan npm/NuGet updates, or assess breaking changes in package updates.
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。
[Git] Use when generating developer KPI, performance, contribution value, story point, man-day, or code-quality reports from local git commit history.
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 Quality] Use when you need to run linters and fix issues for backend or frontend.
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 Quality] Use when you need to validate a PBI against Definition of Ready before grooming.
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。
[Architecture] Use when designing solution architecture across backend, frontend, data & consistency, integration & APIs, deployment, monitoring, testing, and code quality. Architecture laws, style-selection triggers, coupling taxonomy, trade-off tables and the anti-pattern catalog live in `.claude/docs/architecture-knowledge.md`.
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 Quality] Use when reviewing architecture compliance for layers, messaging, service boundaries, CQRS, repos, entity events, and data/consistency/tenancy boundaries. Universal architecture laws, coupling taxonomy and the anti-pattern catalog live in `.claude/docs/architecture-knowledge.md` (project docs always outrank 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。
[Code Quality] Use when you need to combine /changes-review + /fix in a recursive loop — each round runs /changes-review (report-only) to surface validated findings over a fixed diff scope, then /fix to resolve them, then loops again with a FRESH full /changes-review over the CHANGED diff until one complete pass produces zero validated findings (nothing left to fix).
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 needs to update, improve, audit, or maintain documentation in a project. Covers READMEs, changelogs, API docs, inline comments, missing docs, and overall documentation quality. Works well before releases or when documentation has fallen behind the 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。
Use when building or modifying SwiftUI views, settings windows, menu-bar UIs, or any surface for the KIKA app — or any calm, premium app you want to feel the same way. Encodes the KIKA Design System v2 (June 2026) — a calm, premium, modern dark UI with first-class light mode, inspired by Cursor, Linear, and high-quality dev tools — that you can adopt or adapt for your own app. Apply it to keep color, typography, spacing, and component styling consistent.
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。
Full website GEO+SEO audit with parallel agents first and skills fallback. Orchestrates a comprehensive Generative Engine Optimization audit across AI citability, platform analysis, technical infrastructure, content quality, and schema markup. Produces a composite GEO Score (0-100) with prioritized action 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。
GEO-first SEO analysis tool. Optimizes websites for AI-powered search engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) while maintaining traditional SEO foundations. Performs full GEO audits, citability scoring, AI crawler analysis, llms.txt generation, brand mention scanning, platform-specific optimization, schema markup, technical SEO, content quality (E-E-A-T), and client-ready GEO report generation. Use when user says "geo", "seo", "audit", "AI search", "AI visibility", "optimize", "citability", "llms.txt", "schema", "brand mentions", "GEO report", or any URL for analysis.
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。
Content quality and E-E-A-T assessment for AI citability — evaluate experience, expertise, authoritativeness, trustworthiness, and content structure
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 packages for documentation completeness, detect drift between code and docs, and maintain documentation quality across the monorepo. Use when checking package docs, running audits, or reviewing documentation health.
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 distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.
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。
Run convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.
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 distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context.
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。
Run convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.
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。