Topic: claude-skills
11,948 skills in this topic.
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jta
Translate JSON i18n files to multiple languages with AI-powered quality optimization. Use when user mentions translating JSON, i18n files, internationalization, locale files, or needs to convert language files to other languages.
ckanner/agent-skills 21
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prompt-optimizer
This skill should be used when users request help optimizing, improving, or refining their prompts or instructions for AI models. Use this skill when users provide vague, unclear, or poorly structured prompts and need assistance transforming them into clear, effective, and well-structured instructions that AI models can better understand and execute. This skill applies comprehensive prompt engineering best practices to enhance prompt quality, clarity, and effectiveness.
ckanner/agent-skills 21
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context-engineering
Strategies for managing LLM context windows effectively in AI agents. Use when building agents that handle long conversations, multi-step tasks, tool orchestration, or need to maintain coherence across extended interactions.
itsmostafa/llm-engineering-skills 17
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lora
Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specialized models from a single base.
itsmostafa/llm-engineering-skills 17
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mlx
Running and fine-tuning LLMs on Apple Silicon with MLX. Use when working with models locally on Mac, converting Hugging Face models to MLX format, fine-tuning with LoRA/QLoRA on Apple Silicon, or serving models via HTTP API.
itsmostafa/llm-engineering-skills 17
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pytorch
Building and training neural networks with PyTorch. Use when implementing deep learning models, training loops, data pipelines, model optimization with torch.compile, distributed training, or deploying PyTorch models.
itsmostafa/llm-engineering-skills 17
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agents
Patterns and architectures for building AI agents and workflows with LLMs. Use when designing systems that involve tool use, multi-step reasoning, autonomous decision-making, or orchestration of LLM-driven tasks.
itsmostafa/llm-engineering-skills 17
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prompt-engineering
Crafting effective prompts for LLMs. Use when designing prompts, improving output quality, structuring complex instructions, or debugging poor model responses.
itsmostafa/llm-engineering-skills 17
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qlora
Memory-efficient fine-tuning with 4-bit quantization and LoRA adapters. Use when fine-tuning large models (7B+) on consumer GPUs, when VRAM is limited, or when standard LoRA still exceeds memory. Builds on the lora skill.
itsmostafa/llm-engineering-skills 17
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rlhf
Understanding Reinforcement Learning from Human Feedback (RLHF) for aligning language models. Use when learning about preference data, reward modeling, policy optimization, or direct alignment algorithms like DPO.
itsmostafa/llm-engineering-skills 17
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transformers
Loading and using pretrained models with Hugging Face Transformers. Use when working with pretrained models from the Hub, running inference with Pipeline API, fine-tuning models with Trainer, or handling text, vision, audio, and multimodal tasks.
itsmostafa/llm-engineering-skills 17
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critical-code-reviewer
Conduct rigorous, adversarial code reviews with zero tolerance for mediocrity. Use when users ask to "critically review" my code or a PR, "critique my code", "find issues in my code", or "what's wrong with this code". Identifies security holes, lazy patterns, edge case failures, and bad practices across Python, R, JavaScript/TypeScript, SQL, and front-end code. Scrutinizes error handling, type safety, performance, accessibility, and code quality. Provides structured feedback with severity tiers (Blocking, Required, Suggestions) and specific, actionable recommendations.
posit-dev/skills 224
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describe-design
Research a codebase and create architectural documentation describing how features or systems work. Use when the user asks to: (1) Document how a feature works, (2) Create an architecture overview, (3) Explain code structure for onboarding or knowledge transfer, (4) Research and describe a system's design. Produces markdown documents with Mermaid diagrams and stable code references suitable for humans and AI agents.
posit-dev/skills 224
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cli
Comprehensive R package for command-line interface styling, semantic messaging, and user communication. Use this skill when working with R code that needs to: (1) Format console output with inline markup and colors, (2) Display errors, warnings, or messages with cli_abort/cli_warn/cli_inform, (3) Show progress indicators for long-running operations, (4) Create semantic CLI elements (headers, lists, alerts, code blocks), (5) Apply themes and customize output styling, (6) Handle pluralization in user-facing text, (7) Work with ANSI strings, hyperlinks, or custom containers. Also use when migrating from base R message/warning/stop, debugging cli code, or improving existing cli usage.
posit-dev/skills 224
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mirai
Help users write correct R code for async, parallel, and distributed computing using mirai. Use when users need to: run R code asynchronously or in parallel, write mirai code with correct dependency passing, set up local or remote parallel workers, convert code from future or parallel, use parallel map operations, integrate async tasks with Shiny or promises, or configure cluster/HPC computing.
posit-dev/skills 224
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r-cli-app
Build command-line apps in R using the Rapp package. Use when creating a CLI tool in R, adding argument parsing to an R script, turning an R script into a command-line app, shipping CLIs in an R package, or using Rapp (the alternative Rscript front-end). Also use for shebang scripts, exec/ directory in R packages, or subcommand-based R tools.
posit-dev/skills 224
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r-package-development
R package development with devtools, testthat, and roxygen2. Use when the user is working on an R package, running tests, writing documentation, or building package infrastructure.
posit-dev/skills 224
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brand-yml
Create and use brand.yml files for consistent branding across Shiny apps and Quarto documents. Use when working with brand styling, colors, fonts, logos, or corporate identity in Shiny or Quarto projects. Covers: (1) Creating new _brand.yml files from brand guidelines, (2) Applying brand.yml to Shiny for R apps with bslib, (3) Applying brand.yml to Shiny for Python apps with ui.Theme, (4) Using brand.yml in Quarto documents, presentations, dashboards, and PDFs, (5) Modifying existing brand.yml files, (6) Troubleshooting brand integration issues. Includes complete specifications and framework-specific integration guides.
posit-dev/skills 224
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pr-create
Creates a pull request from current changes, monitors GitHub CI, and debugs any failures until CI passes. Use this when the user says "create pr", "make a pr", "open pull request", "submit pr", "pr for these changes", or wants to get their current work into a reviewable PR. Assumes the project uses git, is hosted on GitHub, and has GitHub Actions CI with automated checks (lint, build, tests, etc.). Does NOT merge - stops when CI passes and provides the PR link.
posit-dev/skills 224
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pr-threads-address
Review all unresolved PR review threads, address them by making necessary code changes, and commit the changes appropriately.
posit-dev/skills 224
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pr-threads-resolve
Bulk resolve unresolved PR review threads. Useful after manually addressing threads or after using /pr-threads-address.
posit-dev/skills 224
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quarto-alt-text
Generate accessible alt text for data visualizations in Quarto documents. Use when the user wants to add, improve, or review alt text for figures in .qmd files. Triggers for requests about accessibility, figure descriptions, fig-alt, screen reader support, or making Quarto documents more accessible.
posit-dev/skills 224
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quarto-authoring
Writing and authoring Quarto documents (.qmd), including code cell options, figure and table captions, cross-references, callout blocks (notes, warnings, tips), citations and bibliography, page layout and columns, Mermaid diagrams, YAML metadata configuration, and Quarto extensions. Also covers converting and migrating R Markdown (.Rmd), bookdown, blogdown, xaringan, and distill projects to Quarto, and creating Quarto websites, books, presentations, and reports.
posit-dev/skills 224
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cran-extrachecks
Prepare R packages for CRAN submission by checking for common ad-hoc requirements not caught by devtools::check(). Use when: (1) Preparing a package for first CRAN release, (2) Preparing a package update for CRAN resubmission, (3) Reviewing a package to ensure CRAN compliance, (4) Responding to CRAN reviewer feedback. Covers documentation requirements, DESCRIPTION field standards, URL validation, examples, and administrative requirements.
posit-dev/skills 224