Erold is an AI-native project management platform built specifically for developers and AI agents to collaborate. It features MCP server integration, REST API, CLI tool, and a knowledge base that gives AI persistent memory across sessions.

How does Erold integrate with Claude Code?

Erold provides a native MCP (Model Context Protocol) server with 18 tools that Claude Code can use directly. This allows Claude to create tasks, update progress, access project knowledge, and manage your projects without any copy-paste.

Yes! Erold offers a free tier with 1 project and unlimited tasks. Pro is $5/month with pay-as-you-go pricing for extra resources. Only pay for what you use beyond included allocations.

What AI tools does Erold support?

Erold works with any AI tool that supports MCP or REST APIs, including Claude Code, Claude Desktop, Cursor, Windsurf, GitHub Copilot, and custom AI agents. The API-first design ensures compatibility with current and future AI tools.

What is MCP (Model Context Protocol)?

MCP (Model Context Protocol) is a standard protocol that allows AI assistants to interact with external tools and services. Erold's MCP server provides 18 tools for task management, knowledge base access, and project operations that AI assistants can use directly.

How is Erold different from Jira, Linear, or Asana?

Erold is built API-first for AI agents, not humans-first with APIs added later. Traditional tools require copy-paste to share context with AI. Erold lets AI assistants read tasks, update progress, and access project knowledge directly through MCP, API, or CLI.

What is the Knowledge Base feature?

The Knowledge Base is persistent memory for AI assistants. Store project context, coding standards, architecture decisions, and any information AI should remember across sessions. AI can read and write knowledge entries, making it smarter about your specific project over time.

Does Erold have a CLI tool?

Yes! The Yet CLI (npm install -g @erold/cli) provides full task management from your terminal. Create tasks, list projects, mark items done, and integrate with git workflows. Perfect for developers who prefer command-line tools.

When should I use Code Review Patterns?

Team development. Pull request workflows. Quality assurance. Knowledge sharing

When should I NOT use Code Review Patterns?

Solo projects. Emergency hotfixes. Trivial changes

quality code-review recommended

Code Review Patterns

Best practices for effective code reviews including what to look for, how to give feedback, and automation.

Difficulty: beginner
Read time: 1 min read
Version: v1.0.0
Confidence: established
Last updated: Updated Jan 10, 2026

Edit on GitHub Report Issue

Quick Reference

Code Review: Focus on logic, security, and design - not style (use linters). Keep PRs small (<400 lines). Review within 24h. Be specific and suggest alternatives. Automate what can be automated. Approve with minor comments; block only for significant issues.

Use When

Team development
Pull request workflows
Quality assurance
Knowledge sharing

Skip When

Solo projects
Emergency hotfixes
Trivial changes

Code Review Patterns

Best practices for effective code reviews including what to look for, how to give feedback, and automation.

Discussion

Test Strategy critical SOLID Principles recommended

Code Review Patterns

Quick Reference

Use When

Skip When

Code Review Patterns

Discussion

Strictly Necessary

Analytics

Functional