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概要と使いどころ
Build AI agents with LangChain framework. Use when building agents, tools, memory, MCP integrations, RAG pipelines, multi-agent systems, or any LLM-powered applications using LangChain or LangGraph in Python or TypeScript.
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。
Systematically find and fix performance problems in applications, frontend and backend, by measuring first. Use this skill whenever the user reports slow endpoints, high latency, poor throughput, memory leaks, large bundles, or slow page loads; wants to profile with cProfile, py-spy, Chrome DevTools, Node --cpu-prof, or perf; run load tests with locust or k6; set performance budgets or SLOs; optimize database queries (EXPLAIN, indexes, N+1); add caching (Redis); improve frontend performance (code splitting, lazy loading, image optimization, memoization, virtualization); or tune the network (CDNs, gzip/br, HTTP/2/3). Also trigger for p50/p95/p99 latency, throughput, error rate, connection pooling, async vs threads, GIL, and memory leak investigations.
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。
Find, build, evaluate, and improve systems using decision models. Use for bounded classification, routing, ranking, Choice/Score/Noul, decision-model composition, evaluation harnesses, prompt/program hill climbing, and Software 3.0 workflows across software, business, organizations, and life. Separate models, code, and human judgment. TypeSafe Jev is the default hosted exemplar. Not for straightforward arithmetic, prose rewriting, or provider setup alone.
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 citability scoring and optimization. Analyzes web page content to determine how likely AI systems (ChatGPT, Claude, Perplexity, Gemini) are to cite or quote passages from the page. Provides a citability score (0-100) with specific rewrite suggestions.
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 and generates llms.txt files -- the emerging standard for helping AI systems understand website structure and content. Can validate existing llms.txt files or generate new ones from scratch by crawling the site.
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。
Manages brand identity, visual design system, and creative quality for MMIND.ai. Generates complete image prompts for Nano Banana Pro (Gemini), enforces the strict 5-color palette, flat-vector SaaS style, and typography standards. Use when user needs graphic prompts, brand consistency checks, visual style guidance, design briefs, or creative QA for any marketing asset.
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。
Systematic testing methodology for exhaustive branch coverage, edge case identification, and production bug prevention. Use when PR review reveals incomplete test coverage, when tests pass but users report bugs, when code changes break existing features, when verifying all branches and edge cases before merge, when analyzing "it works on my machine" issues, when planning test strategy for new features, or when debugging flaky tests and race conditions.
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。
Enforce traceability from natural-language intent to machine predicates, final observables, evidence, and owner-readable acceptance. Use when conducting any audit, review, QA pass, parity or compliance check, security assessment, code or architecture review, visual or behavioral comparison, data validation, system verification, completion gate, or claim that an implementation satisfies a human request.
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 selecting serialisation formats and contracts for APIs, messaging, caching, or persistence. Keywords: serialisation, System.Text.Json, source generator, protobuf, messagepack, wire compatibility, AOT.
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。
Diagnose and fix CJK (Korean, Japanese, Chinese) text-wrapping issues in web UIs. Systematically traces mid-syllable breaks, orphaned glyphs, and awkward line splits through a layered fix strategy covering global CSS cascade, component-library overrides, headline balancing, and translation-level phrase binding. Produces an evidence-based diagnosis and verification report before any code change is applied.
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。
Finds and quotes TypeSafe's docs on Jev, including Noul, Choice, Score and Box questions, models and limits. Use when a question, review, design or claim involves Jev or System One, when briefing a subagent on Jev work, or when relaying a subagent's Jev finding.
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 rating whether a project, repo, skill, workflow, plugin, agent product or post uses TypeSafe's Jev (System One) model well -- "is this a good use of Jev?", "rate this Jev integration", "jevaluate <url>", or a link to something named after Jev; also when checking whether something that calls itself Jev actually uses 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。
Use on a bug, test failure, crash, or unexpected behavior — enforce reproduce → isolate → hypothesize → verify before any fix; fires even on 'this is broken' / 'quick 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 for deep Laravel project analysis: boot flow, request lifecycle, container usage, Eloquent/data flow, async systems, and Laravel-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 designing production-LLM prompts — few-shot, chain-of-thought, system prompts, templates, self-verification — distinct from prompt-optimizer and refine-prompt.
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。
Build a slide presentation as one HTML file — fixed 1920×1080 canvas letterboxed to any viewport, layout-system-first, type floors. Use for deck, slides, presentation, or pitch requests.
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。
Author a 3-layer DTCG token system (primitive → semantic → component) with light/dark theming; generate CSS vars + Tailwind colors and lint hardcoded values. Use on design tokens / CSS variables.
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。
Write and maintain DESIGN.md + PRODUCT.md — captures visual decisions and interaction patterns so design tasks stay consistent across sessions without re-scanning past 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。
Use when a diff may break system boundaries, dependency direction, or cross-service contracts — fifth judge dispatched by /review-changes alongside the four standard judges.
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 mapping funnel-stage to content shape — conversion-pathway, content-as-system, leverage-point selection. Triggers on 'design our content funnel', 'why does mid-funnel leak'.
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。
Boot the explicitly selected CLI(s) as the human's concierge: a project-aware side channel that sits ABOVE the running agent system in a shared writable terminal. It answers status questions and handles the human's ad hoc tasking while the working agents collaborate on the mesh — it is not a worker, manager, or gatekeeper, and team progress never waits for 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。
Kit de ferramentas de sistema de design de UI para Designer de UI Sênior, incluindo geração de design tokens, documentação de componentes, cálculos de design responsivo e ferramentas de handoff para desenvolvimento. Use para criar sistemas de design, manter consistência visual e facilitar colaboração entre design e desenvolvimento.
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 tem o maior ROI de qualquer canal de marketing. R$ 36 para cada R$ 1 gasto. Mas a maioria das startups trata como secundário - envios em massa, sem personalização, caindo em spam. Esta skill cobre email transacional que funciona, automação de marketing que converte, entregabilidade que atinge caixas de entrada, e decisões de infraestrutura que escalam. Use quando: keywords, file_patterns, code_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。
Especialista em design de prompts eficazes para aplicações com LLM. Domina estrutura de prompts, gerenciamento de contexto, formatação de output e avaliação de prompts. Use quando: engenharia de prompts, system prompt, few-shot, chain of thought, design de prompts.
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。