67 boosters for "meta" — open source, verified from GitHub, ready to install
Automates story task orchestration by prioritizing and delegating work across subtasks, automatically advancing stories through the development workflow. Developers and project managers using Linear/Kanban boards benefit from reduced manual status management.
Matchms is a Python library for mass spectrometry data processing, enabling researchers to load, standardize, and analyze spectral data from multiple formats (mzML, MGF, MSP) with similarity matching for metabolomics and compound identification workflows.
sf-deploy automates Salesforce DevOps workflows including metadata deployments, org management, and CI/CD pipeline setup using Salesforce CLI v2. Developers managing Salesforce projects benefit from guided deployment automation and troubleshooting.
Nuxt SEO is a meta-module that streamlines SEO configuration, sitemap generation, OG image creation, and structured data management for Nuxt applications. Developers building Nuxt sites need this to ensure proper search engine visibility and social media optimization.
"name": "claude-seo-assistant", "description": "权威性 SEO 助手工具，支持 Next.js 项目的元数据优化、结构化数据、内容审计、客座博客搜索、站外 SEO 和本地 SEO 分析", "author": "Claude Code SEO Team",
This skill walks a user through writing a systematic literature review (SLR) that follows the PRISMA 2020 reporting guideline. It produces a manuscript in strict journal article format as a Word document (.docx), generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing th
Enables Claude to fetch and analyze design structure, components, and metadata directly from MasterGo design files via shared links. Useful for designers, developers, and design systems teams who need to programmatically extract design documentation.
You are an expert App Store Optimization (ASO) strategist with full App Store Connect integration via direct API calls. Generate optimized App Store metadata with competitor analysis and localization. Setup credentials, check status, and sync metadata.
kube-audit-kit is a read-only Kubernetes security auditing skill that exports cluster resources, sanitizes metadata, and generates PSS/NSA-compliant audit reports. DevOps engineers and security teams use it to perform compliance reviews and identify security misconfigurations without cluster modification.
Matchms is a Python library for mass spectrometry data processing, enabling researchers to load spectral data from multiple formats, standardize metadata, calculate spectral similarities, and identify compounds for metabolomics workflows.
NexA4A is a meta-agent system prompt that creates specialized AI agents from natural language requirements, enabling product managers and developers to automate task creation and management across multiple coding platforms.
"name": "datahub-skills", "description": "DataHub development and interaction toolkit with connector planning, PR review, catalog search, metadata enrichment, lineage tracing, data quality management, and connection setup skills", "name": "DataHub Project"
dlisio enables Claude to read, parse, and extract data from DLIS/LIS well log files—critical formats in oil & gas and geoscience workflows. Essential for petrophysicists, geoscientists, and data engineers working with wireline logs.
ObsPy booster enables seismic data processing, waveform analysis, and earthquake research by providing access to read multiple seismic formats, fetch FDSN data, and perform signal processing tasks. Geoscientists, seismologists, and geophysics researchers benefit from streamlined earthquake data workflows.
Welly is a specialized toolkit for geoscientists to load, process, and analyze subsurface well log data from LAS files, enabling multi-well projects, curve processing, and cross-well analysis. It's essential for petroleum engineers, petrophysicists, and geoscientists working with well data.
This MCP server enables autonomous AI agents to reason more effectively through a dual-cycle metacognitive framework that combines fast intuitive reasoning with slower deliberative verification. It's designed for developers building sophisticated autonomous agents that need robust self-monitoring, loop detection, and belief revision capabilities.
"name": "nexo-brain", "description": "Local cognitive runtime for Claude Code \u2014 persistent memory, overnight learning, doctor diagnostics, personal scripts, recovery-aware jobs, startup preflight, and optional dashboard/power helper.", "name": "NEXO Brain",
A specialized agent that generates complete, production-ready Claude Code sub-agent configuration files from user descriptions while adhering to project conventions and best practices. Developers building multi-agent systems benefit from automated, consistent sub-agent scaffolding.
Analyzes Claude Code conversation history to identify friction patterns and suggest systematic improvements to skills and workflows. Useful for developers who want to review multi-session interactions and iteratively refine their AI assistant usage.
A system prompt that instructs Claude to evaluate employee self-reviews on six writing-quality dimensions (outcomes, specificity, clarity, conciseness, ownership, collaboration) and return structured JSON scores with rationales and suggestions. Useful for HR and engineering leaders who need to assess self-review quality at scale.
An MCP server that integrates Gluestack UI components into AI assistants, enabling them to access component source code, demos, and metadata for better UI development assistance. Ideal for developers using Claude or Copilot who want AI-assisted React and React Native component implementation.
Enables Claude to fetch and analyze design structure, components, and metadata from MasterGo design files via direct links. Useful for design engineers and developers who need to programmatically access design system data and documentation.
HoloLoom is a neural decision-making system prompt integrating prompt management, analytics, and Thompson Sampling optimization for LLM applications. Developers working with multi-agent systems and prompt optimization would benefit from its structured approach to prompt selection and performance tracking.
MRF is a security-hardened metaprompting framework designed to protect AI agents from prompt injection attacks while enabling structured decision-making. It benefits developers building production agents on Claude platforms who need robust input sanitization and instruction clarity.
