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Found 211 Skills
Work with state-of-the-art machine learning models for NLP, computer vision, audio, and multimodal tasks using HuggingFace Transformers. This skill should be used when fine-tuning pre-trained models, performing inference with pipelines, generating text, training sequence models, or working with BERT, GPT, T5, ViT, and other transformer architectures. Covers model loading, tokenization, training with Trainer API, text generation strategies, and task-specific patterns for classification, NER, QA, summarization, translation, and image tasks. (plugin:scientific-packages@claude-scientific-skills)
Z.ai API integration for building applications with GLM models. Use when working with Z.ai/ZhipuAI APIs for: (1) Chat completions with GLM-4.7/4.6/4.5 models, (2) Vision/multimodal tasks with GLM-4.6V, (3) Image generation with GLM-Image or CogView-4, (4) Video generation with CogVideoX-3 or Vidu models, (5) Audio transcription with GLM-ASR-2512, (6) Function calling and tool use, (7) Web search integration, (8) Translation, slide/poster generation agents. Triggers: Z.ai, ZhipuAI, GLM, BigModel, Zhipu, CogVideoX, CogView, Vidu.
Next.js 16 internationalization with next-intl or DIY. Use when implementing i18n, translations, localization, multilingual, language switch, locale routing, or formatters.
Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Translate text between English and Indian languages using Sarvam AI's Mayura model. Use when the user needs to translate content, localize applications, or convert text between Hindi, Tamil, Bengali, Telugu, and 7 other Indian languages. Supports bidirectional translation, script control, and code-mixed text.
When the user wants to translate content, create translation workflows, manage terminology, or optimize translation quality. Also use when the user mentions "translate," "translation," "localization copy," "glossary," "terminology," "style guide translation," "machine translation," "human translation," "TMS," or "multilingual content."
Translate English or Japanese tech articles and texts into natural, fluent Chinese. Use this skill when the user wants to translate text to Chinese, asks for Chinese translation, mentions "translate to Chinese", "翻译", provides English/Japanese tech content for translation, or wants any text converted into Chinese. Also trigger when the user pastes text and asks to translate it, or references a file to translate into Chinese.
(Public Preview) Perform code upgrades, migrations, codebase analysis, and transformations using AWS Transform custom. Use this skill when a user asks to upgrade, migrate, modernize, analyze, or transform code across a repository. ATX supports any-to-any transformations including language version upgrades (Java, Python, Node.js, Ruby, Go, .NET, etc.), framework upgrades and migrations (Spring Boot, React, Angular, Django, etc.), API and SDK migrations (AWS SDK v1 to v2, boto2 to boto3, JS SDK v2 to v3), library upgrades, code refactoring, architecture migrations (x86 to Graviton/ARM64), language-to-language translations, and custom organization-specific transformations. Executes transformations locally on the user's machine using the ATX CLI. Always use the ATX CLI following the reference files — never attempt to modify code, upgrade dependencies, or run analysis manually.
Translate files (PDF, DOCX, PPTX) to any language using the Bluente Translation API. Asks for API key, source files, target language, and output location.
Helps engineering managers measure and improve team delivery — produces a history of why common metrics fail, the DORA four-key-metrics framework (deployment frequency, lead time, change failure rate, MTTR), DevEx's three dimensions (feedback loops, cognitive load, flow state), a translation layer from engineering metrics to business outcomes, and a list of measurement anti-patterns to avoid. Use when the user says "how do I measure productivity," "DORA metrics," "velocity," "cycle time," "developer experience," "DevEx," "how do I show our team is performing well," "metrics for engineering," "team is slow," "engineering performance," or "connect engineering to business." Do NOT use for managing an underperforming individual — use performance-reviews instead.
Migration guide for developers moving from Google Maps Platform to Mapbox GL JS, covering API equivalents, pattern translations, and key differences