agentic-eval
FreePatterns and techniques for evaluating and improving AI agent outputs.
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GitHub MCP Server integration for repository operations, pull requests, issues, and GitHub Actions. Triggers on: github mcp, github operations, pull request, issue, repository, github actions, commit, branch, merge.
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Review the instructions the agent will receive before you install.
Access GitHub repositories, pull requests, issues, and GitHub Actions via the Model Context Protocol (MCP).
The GitHub MCP Server enables AI agents to interact with GitHub programmatically. It provides tools for repository operations, code review, issue management, and CI/CD pipeline inspection.
The MCP server is configured in .rulesync/mcp.json:
{
"mcpServers": {
"github": {
"type": "remote",
"url": "https://api.githubcopilot.com/mcp/",
"oauth": false,
"headers": {
"Authorization": "Bearer {env:GITHUB_TOKEN}"
},
"enabled": true
}
}
}
Prerequisites: Set
GITHUB_TOKENenvironment variable with a GitHub Personal Access Token.
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Patterns and techniques for evaluating and improving AI agent outputs.
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Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations.
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Use when user requests research requiring multiple sources, comprehensive analysis, or synthesis across topics - technical research, domain knowledge gathering, market analysis, or learning about complex subjects
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AI-powered wiki generation for code repositories with commands, agents, and skills
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Use when building .NET 10 or C# 14 applications; when using minimal APIs, modular monolith patterns, or feature folders; when implementing HTTP resilience, Options pattern, Channels, or validation; when seeing outdated patterns like old extension method syntax
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Implements accessible .NET UI. SemanticProperties, ARIA, AutomationPeer, testing per platform.
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