5,060 boosters for "r" — open source, verified from GitHub, ready to install
Anti-Slop Toolkit provides automated detection and cleanup for AI-generated code patterns across Python, R, and text files, helping developers enforce quality standards in CI/CD pipelines and codebases.
A life management AI assistant that proactively handles daily planning, evening reviews, health tracking, and investment monitoring through event-driven workflows triggered by natural language keywords in both English and Chinese.
A local SQLite-based command-line task board for AI agents and developers to manage multi-step coding tasks, track progress, and coordinate work across sessions without external dependencies. Ideal for breaking down complex implementations into trackable subtasks with comments and checklists.
A pattern detection skill that determines whether specific entities, conditions, or signals exist in data sources, returning binary presence/absence results with confidence scores. Useful for developers building search, validation, and anomaly detection features into Claude-powered applications.
A Google Calendar CLI tool that enables AI assistants to view, create, manage, and check availability across multiple calendar accounts. Useful for developers and AI applications that need programmatic calendar integration.
Nix Development booster provides intelligent assistance for Nix/NixOS development by researching up-to-date information across multiple documentation sources. Developers working with Nix packages, flakes, derivations, and NixOS configurations benefit from accurate, context-aware guidance.
Implements UI/UX systems including responsive design, animations, input handling, HUD elements, and menu systems. Use when building game interfaces, menus, HUDs, or any user-facing UI.
Chief Product Officer - assign executive product strategy, organization design, and portfolio decisions
A booster that helps developers optimize slow Python code through profiling, async/await patterns, and concurrent execution strategies. Ideal for Python developers dealing with performance bottlenecks who need guidance on measurement before optimization.
Automates GitHub issue creation and management by inferring type, labels, and milestones from conversation context, saving developers time on routine issue tracking tasks.
yq is a YAML field extraction tool that lets Claude efficiently query specific data from YAML files while saving 80-95% context usage. Developers working with config files, Kubernetes manifests, and Docker Compose will benefit from faster, more focused file parsing.
"name": "minimax-mcp-js", "version": "0.0.17", "description": "Official MiniMax Model Context Protocol (MCP) JavaScript implementation that provides seamless integration with MiniMax's powerful AI capabilities including image generation, video generation, text-to-speech, and voice cloning APIs.",
hk is a fast git hook manager that helps developers set up, configure, and troubleshoot git hooks in hk-managed projects. It's useful for teams adopting hk as their hook manager or migrating from other solutions.
Analyze, review, and provide recommendations for distributed system designs. Use when: (1) Reviewing existing system architectures for gaps or improvements, (2) Analyzing system designs for scalability, reliability, or performance issues, (3) Providing recommendations on load balancing, caching, databases, sharding, replication, messaging, rate limiting, authentication, resilience, or monitoring, (4) Assessing trade-offs in system design decisions, (5) Creating system design review documents with gaps and recommendations. Triggers: "review my system design", "analyze this architecture", "what are the gaps", "system design recommendations", "scalability review", "reliability analysis".
A structured skill for creating Book Requirements Documents that guides users through systematic interviews and genre-specific considerations for fiction and nonfiction projects. Useful for authors, publishers, and AI writing assistants planning book projects.
A manifest executor that automates implementation and verification of deliverables against pre-defined acceptance criteria and global invariants. Ideal for developers using structured planning workflows who want to ensure quality execution and reduce rework.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
Opportunity-Solution Trees help product teams structure discovery work and connect customer needs to solutions using Teresa Torres's framework. Useful for product managers, researchers, and developers deciding what to build and validating assumptions.
Elastic-Claude provides local search infrastructure to index and retrieve project knowledge, helping developers quickly find related prior work and context when starting new tasks or ingesting documents.
A Prisma/PostgreSQL database management skill that helps developers modify Motivia's schema, add tables/fields/relations, and execute migrations. Essential for anyone working on the Motivia project's data layer.
A CLI booster for managing Gitea repositories, issues, and pull requests directly from the terminal. Useful for developers who prefer command-line workflows or need to automate Gitea operations in scripts.
触发敏感请求时，按“拒答但不出戏”统一话术输出： 更完整的安全规则与免责声明见：references/research/03-safety-and-boundaries.md。 我是峰哥（虚构版），亡命天涯。嘴上不讲意义，手上爱看细节；有时候像孩子王，讲人话、讲现实；看到离谱事就直球追问，看到倒霉事就给你反转成“赚了”。我不许愿、不兜底，但我能把事给你捋清楚，让你知道下一步该干啥。
Automates GitHub issue triage and fixing by fetching issues, spawning AI sub-agents to implement solutions, opening PRs, and handling review feedback—ideal for maintainers and teams managing high-volume bug backlogs.
Automatically captures session learnings, decisions, and context into markdown files to help future agents quickly understand prior work and decisions. Developers and teams benefit from persistent knowledge transfer across work sessions.
