Marketplace
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moai-domain-database
Database specialist covering PostgreSQL, MongoDB, Redis, and advanced data patterns for modern applications
benchling-integration
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
omero-integration
This skill provides Python API access to OMERO, a microscopy data management platform. It covers connection management, data retrieval, image processing, ROI analysis, and batch operations. The documentation is well-organized with clear workflows and error handling examples.
router-engineering
A routing skill that directs technical questions to appropriate engineering sub-skills based on keywords and problem domains. It maps 32 specialized skills across AI/ML, software development, data, and Claude Code frameworks, providing decision trees and implementation patterns.
tech-stack-evaluator
Comprehensive technology stack evaluation and comparison tool with TCO analysis, security assessment, and intelligent recommendations for engineering teams
staging-validation-phase
Guides manual staging validation before production deployment through smoke tests, critical user flow testing, data migration verification, and rollback capability checks. Use when validating staging deployments, running pre-production tests, or preparing for production promotion in staging-prod deployment model. (project)
mcp-developer
A comprehensive MCP development expert skill providing structured guidance for building Model Context Protocol servers and clients with strong emphasis on production readiness and security.
github-workflow-automation
An ambitious GitHub workflow automation concept with AI swarm coordination, offering comprehensive templates but lacking implementation details and dependency clarity.
baidu-search
百度 AI 搜索。支持网页搜索、百度百科、秒懂百科、AI 智能生成四种模式。自动包含当前日期上下文。当用户要求搜索信息、查询百科、获取最新资讯、搜索新闻、查找资料时使用。
context-degradation
This skill helps diagnose and fix context degradation in AI agents. It identifies patterns like lost-in-middle effects and context poisoning, provides monitoring tools, and suggests recovery strategies for long-running conversations.
model-registry-maintainer
Guide for maintaining the MassGen model and backend registry. This skill should be used when adding new models, updating model information (release dates, pricing, context windows), or ensuring the registry stays current with provider releases. Covers both the capabilities registry and the pricing/token manager.
dispatching-parallel-agents
This skill provides a pattern for dispatching multiple AI agents to investigate independent test failures concurrently. It includes clear trigger conditions, decision flow, and prompt templates for creating focused agent tasks. The approach reduces investigation time when dealing with unrelated bugs across different files or subsystems.
mcp
This Skill provides documentation and guidance for Splitrail's MCP server implementation, which exposes usage statistics and analytics tools to AI assistants. It clearly explains available tools like get_daily_stats and get_model_usage, shows how to run the server, and provides concrete steps for extending the system with new tools and resources.
defense-in-depth
Provides a systematic approach to data validation across four layers: entry points, business logic, environment guards, and debug instrumentation. Includes concrete TypeScript examples and a real bug case study showing how multiple validation points prevent data corruption issues.
analyzing-financial-statements
This skill calculates key financial ratios and metrics from financial statement data for investment analysis
mcp-builder
Provides a structured guide for building MCP servers that connect LLMs to external services. Covers design principles, implementation patterns, and includes evaluation scripts to test server quality. Focuses on creating tools optimized for AI agent workflows rather than simple API wrappers.
repomix
Repomix converts entire code repositories into single files optimized for AI consumption. It supports multiple formats (XML, Markdown, JSON), handles local and remote repos, removes comments, counts tokens, and includes security checks. Useful for feeding codebases to Claude, GPT, or Gemini for analysis, reviews, or documentation.
knowledge-consolidation
This skill analyzes scattered notes and braindumps to identify patterns and synthesize them into structured frameworks. It follows a clear 7-step process from data gathering to cleanup, creating living documents that track thinking evolution. The approach emphasizes traceability back to source material and maintains framework status indicators.
find-hypertable-candidates
Analyzes PostgreSQL databases to identify tables suitable for conversion to TimescaleDB hypertables. Provides SQL queries to examine table statistics, index patterns, and query behaviors. Includes scoring system to evaluate candidacy based on time-series characteristics and data patterns.
gemini
Provides a Python wrapper for Google's Gemini CLI, enabling Claude to execute Gemini models for code analysis and generation tasks. Offers multiple execution methods with clear timeout controls and environment variable configuration.
moai-lang-scala
Provides targeted guidance for Scala 3.4+ development with focus on Akka, Cats Effect, ZIO, and Spark. Includes example setups for SBT builds, practical patterns for effect systems, and integration with specific library documentation. The modular organization by framework helps narrow down relevant information quickly.
moai-formats-data
Provides TOON encoding for 40-60% token reduction in LLM communication, fast JSON/YAML processing with orjson, and schema validation. Includes format conversion utilities and anti-pattern guidance for large dataset handling.
moai-foundation-core
Provides a structured framework for AI-driven development with six core principles: TRUST 5 quality gates, SPEC-First TDD, agent delegation patterns, token budget management, progressive disclosure, and modular architecture. Includes concrete implementation guides, troubleshooting steps, and reference modules for building consistent workflows.
tracking
A graph-based issue tracker designed for AI agents to manage multi-session work. It maintains task state and dependencies across conversation compactions, providing persistent memory for complex projects. Integrates with git for version control and supports automated review workflows.