Back to Skills

moai-lang-sql

modu-ai
Updated 4 days ago
21 views
424
78
424
View on GitHub
Otherai

About

This skill provides SQL best practices enforcement using pgTAP for testing, sqlfluff 3.2 for linting, query optimization, and migration management. It automatically activates during SQL-related discussions and file patterns, supporting TDD workflows and PostgreSQL/MySQL databases. Developers should use it for maintaining SQL code quality and implementing database testing standards.

Quick Install

Claude Code

Recommended
Plugin CommandRecommended
/plugin add https://github.com/modu-ai/moai-adk
Git CloneAlternative
git clone https://github.com/modu-ai/moai-adk.git ~/.claude/skills/moai-lang-sql

Copy and paste this command in Claude Code to install this skill

Documentation

Lang Sql Skill

Skill Metadata

FieldValue
Skill Namemoai-lang-sql
Version2.0.0 (2025-10-22)
Allowed toolsRead (read_file), Bash (terminal)
Auto-loadOn demand when keywords detected
TierLanguage

What It Does

SQL best practices with pgTAP, sqlfluff 3.2, query optimization, and migration management.

Key capabilities:

  • ✅ Best practices enforcement for language domain
  • ✅ TRUST 5 principles integration
  • ✅ Latest tool versions (2025-10-22)
  • ✅ TDD workflow support

When to Use

Automatic triggers:

  • Related code discussions and file patterns
  • SPEC implementation (/alfred:2-run)
  • Code review requests

Manual invocation:

  • Review code for TRUST 5 compliance
  • Design new features
  • Troubleshoot issues

Tool Version Matrix (2025-10-22)

ToolVersionPurposeStatus
PostgreSQL17.2Primary✅ Current
MySQL9.1.0Primary✅ Current
sqlfluff3.2.5Primary✅ Current
pgTAP1.3.3Primary✅ Current

Inputs

  • Language-specific source directories
  • Configuration files
  • Test suites and sample data

Outputs

  • Test/lint execution plan
  • TRUST 5 review checkpoints
  • Migration guidance

Failure Modes

  • When required tools are not installed
  • When dependencies are missing
  • When test coverage falls below 85%

Dependencies

  • Access to project files via Read/Bash tools
  • Integration with moai-foundation-langs for language detection
  • Integration with moai-foundation-trust for quality gates

References (Latest Documentation)

Documentation links updated 2025-10-22


Changelog

  • v2.0.0 (2025-10-22): Major update with latest tool versions, comprehensive best practices, TRUST 5 integration
  • v1.0.0 (2025-03-29): Initial Skill release

Works Well With

  • moai-foundation-trust (quality gates)
  • moai-alfred-code-reviewer (code review)
  • moai-essentials-debug (debugging support)

Best Practices

DO:

  • Follow language best practices
  • Use latest stable tool versions
  • Maintain test coverage ≥85%
  • Document all public APIs

DON'T:

  • Skip quality gates
  • Use deprecated tools
  • Ignore security warnings
  • Mix testing frameworks

GitHub Repository

modu-ai/moai-adk
Path: .claude/skills/moai-lang-sql
agentic-aiagentic-codingagentic-workflowclaudeclaudecodevibe-coding

Related Skills

sglang

Meta

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

View skill

evaluating-llms-harness

Testing

This Claude Skill runs the lm-evaluation-harness to benchmark LLMs across 60+ standardized academic tasks like MMLU and GSM8K. It's designed for developers to compare model quality, track training progress, or report academic results. The tool supports various backends including HuggingFace and vLLM models.

View skill

llamaguard

Other

LlamaGuard is Meta's 7-8B parameter model for moderating LLM inputs and outputs across six safety categories like violence and hate speech. It offers 94-95% accuracy and can be deployed using vLLM, Hugging Face, or Amazon SageMaker. Use this skill to easily integrate content filtering and safety guardrails into your AI applications.

View skill

langchain

Meta

LangChain is a framework for building LLM applications using agents, chains, and RAG pipelines. It supports multiple LLM providers, offers 500+ integrations, and includes features like tool calling and memory management. Use it for rapid prototyping and deploying production systems like chatbots, autonomous agents, and question-answering services.

View skill