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Ferramentas são como agentes de IA interagem com o mundo. Uma ferramenta bem projetada é a diferença entre um agente que funciona e um que alucina, falha silenciosamente ou custa 10x mais tokens do que o necessário. Esta skill cobre design de ferramentas desde schema até tratamento de erros. Melhores práticas em JSON Schema, escrita de descrições que realmente ajudam o LLM, validação e o emerging padrão MCP que está se tornando a língua franca para ferramentas de IA. Insight-chave: Descrições de ferramentas são mais importantes que implementação

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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.

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Testes e benchmarking de agentes LLM incluindo testes comportamentais, avaliação de capacidades, métricas de confiabilidade e monitoramento em produção—onde até os melhores agentes alcançam menos de 50% em benchmarks do mundo real. Use quando: testes de agentes, avaliação de agentes, benchmark de agentes, confiabilidade de agentes, teste de agentes.

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Use this Canvas-owned clean-room skill for creating, reading, editing, reviewing, redlining, commenting, or repairing Word `.docx` documents. Trigger for Word documents, DOCX files, memos, reports, letters, templates, tracked changes, comments, table of contents, headers, footers, page numbers, and Google Docs-targeted documents that should be authored as DOCX first.

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Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

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 this Canvas-owned clean-room skill whenever a PowerPoint `.pptx` deck is an input or output. Trigger for creating, editing, reviewing, repairing, templating, combining, splitting, rendering, or extracting slide decks, including pitch decks, reports, speaker notes, template-following, and Google Slides-targeted handoff.

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Creates a new Angular app using the Angular CLI. This skill should be used whenever a user wants to create a new Angular application and contains important guidelines for how to effectively create a modern Angular application.

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 whenever the project contains navigation components — primary navigation menus, dropdown menus, mega menus, breadcrumbs, pagination, mobile hamburger menus, or in-page jump navigation. Under no circumstances create navigation without proper landmark roles, keyboard support, and accessible labels. Absolutely always wrap navigation in <nav> with a unique aria-label.

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Load this skill whenever the project supports light/dark mode, colour theme switching, high-contrast mode, or responds to prefers-color-scheme. Under no circumstances hard-code colours that break in alternative themes. Absolutely always test colour contrast in both light and dark themes, and respect user OS-level colour preferences via CSS media queries.

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Load this skill whenever the project must support speech input or voice control — dictation, "click by voice" grammars, Dragon NaturallySpeaking, Voice Control (iOS/macOS), Voice Access (Android), or any interface where users activate controls by speaking. Under no circumstances let an aria-label override a visible label without keeping the visible text intact and in order. Absolutely always ensure the accessible name contains the visible label, and load alongside keyboard/SKILL.md since speech tools commonly emulate keyboard and pointer input.

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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.

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Use when the user reports a hard bug, unexpected failure, or performance regression that needs root-cause 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。

Designs an end-to-end process for finding, extracting, enriching, qualifying, and exporting leads. Use when the user wants a repeatable lead workflow plan rather than a single source plan.

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Ranks companies or accounts by strategic relevance and opportunity. Use when the user provides accounts and wants a priority score, tier, rationale, risks, and next action.

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Normalizes and improves the consistency of prospect-list data. Use when the user provides a messy prospect or lead export and wants standardized records, flagged issues, and a cleanup summary.

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Kova/OpenClaw validation: benchmarks, release gates, scenarios, perf reports.

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Use the Crabbox wrapper for OpenClaw remote validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.

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Use when the user adds a project to the workspace, opens an unfamiliar repo, asks "what is this project", "explain this codebase", or invokes explain-new-project. Explores a newly opened workspace project and writes a plain-language report for a self-taught, non-technical user—quick start (what it is + how to run) first, then optional depth—and always saves PROJECT_GUIDE.md in the project root.

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Use when returning to a repo after a break, asking what changed, what's new for this stack, or invoking project-catch-up after explain-new-project. Scans the stack for important updates, deprecations, new helper tools, agent skills, and MCP servers online—plain-language brief saved as PROJECT_CATCH_UP.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。

生成中文职场汇报材料。当用户要"写周报""做月度总结""述职报告""项目汇报""向老板汇报""做汇报PPT大纲""写工作计划"时使用。按结论先行、数据支撑的中文职场表达习惯组织。

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。

Search the web with LLM-optimized results via the Tavily CLI. Use this skill when the user wants to search the web, find articles, look up information, get recent news, discover sources, or says "search for", "find me", "look up", "what's the latest on", "find articles about", or needs current information from the internet. Returns relevant results with content snippets, relevance scores, and metadata — optimized for LLM consumption. Supports domain filtering, time ranges, and multiple search depths.

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Transforms data into compelling visual narratives by applying narrative structure, annotation techniques, scrollytelling patterns, and honest framing to data journalism, presentations, and infographics. Use when creating data-driven articles or reports, designing infographics with narrative, building scrollytelling experiences, annotating charts to guide interpretation, or when user mentions data storytelling, presentation design, annotated chart, narrative visualization.

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。

Convert documents to Markdown using Microsoft's MarkItDown CLI (`markitdown`). Supports PDF, Word, PowerPoint, Excel, images (OCR), audio (transcription), HTML, YouTube, and URLs. Use when a user wants to convert a file or URL to Markdown, extract text from PDFs/images, transcribe audio/video, or batch-convert documents.

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Produce comprehensive synthesis with explicit citations from multiple ordinary public-web sources via the Tavily CLI. Use for detailed reports, comparisons, market or literature research, and questions whose answer requires multi-source web evidence rather than a quick lookup. Do not use for simple discovery (tavily-search), one known URL (tavily-extract), one-site URL discovery or bulk extraction (tavily-map/crawl), or research centered on named social, community, career, code, media, authenticated, or cross-platform sources (Agent Reach). Takes 30-120 seconds.

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。