analyze_github_repository

Analyze a GitHub repository to generate a beginner-friendly tutorial using the PocketFlow methodology, focusing on key abstractions and file patterns for clarity and simplicity.

Instructions

Analyze a GitHub repository and generate a comprehensive tutorial following the PocketFlow methodology

Input Schema

Name	Required	Description	Default
`api_key`	Yes	API key for the LLM provider
`exclude_patterns`	No	File patterns to exclude (e.g., ["test", "docs/"])
`github_token`	No	Optional GitHub token for private repos or rate limit avoidance
`include_patterns`	No	File patterns to include (e.g., [".py", ".js"])
`language`	No	Language for tutorial generation	english
`llm_provider`	Yes	LLM provider to use for analysis	google
`max_abstractions`	No	Maximum number of abstractions to identify
`max_file_size`	No	Maximum file size in bytes
`model`	No	Specific model to use (e.g., "anthropic/claude-3.5-sonnet" for OpenRouter or "gemini-2.5-pro" for Google)	gemini-2.5-pro
`project_name`	No	Optional project name (derived from repo if omitted)
`repo_url`	Yes	GitHub repository URL (e.g., https://github.com/user/repo)
`use_cache`	No	Enable LLM response caching

Input Schema (JSON Schema)

{
  "properties": {
    "api_key": {
      "description": "API key for the LLM provider",
      "type": "string"
    },
    "exclude_patterns": {
      "default": [
        "*test*",
        "*docs/*",
        "*node_modules/*",
        "*.log"
      ],
      "description": "File patterns to exclude (e.g., [\"*test*\", \"*docs/*\"])",
      "items": {
        "type": "string"
      },
      "type": "array"
    },
    "github_token": {
      "description": "Optional GitHub token for private repos or rate limit avoidance",
      "type": "string"
    },
    "include_patterns": {
      "default": [
        "*.py",
        "*.js",
        "*.jsx",
        "*.ts",
        "*.tsx",
        "*.go",
        "*.java",
        "*.md"
      ],
      "description": "File patterns to include (e.g., [\"*.py\", \"*.js\"])",
      "items": {
        "type": "string"
      },
      "type": "array"
    },
    "language": {
      "default": "english",
      "description": "Language for tutorial generation",
      "type": "string"
    },
    "llm_provider": {
      "default": "google",
      "description": "LLM provider to use for analysis",
      "enum": [
        "openrouter",
        "google",
        "anthropic",
        "openai"
      ],
      "type": "string"
    },
    "max_abstractions": {
      "default": 10,
      "description": "Maximum number of abstractions to identify",
      "maximum": 20,
      "minimum": 3,
      "type": "number"
    },
    "max_file_size": {
      "default": 100000,
      "description": "Maximum file size in bytes",
      "type": "number"
    },
    "model": {
      "default": "gemini-2.5-pro",
      "description": "Specific model to use (e.g., \"anthropic/claude-3.5-sonnet\" for OpenRouter or \"gemini-2.5-pro\" for Google)",
      "type": "string"
    },
    "project_name": {
      "description": "Optional project name (derived from repo if omitted)",
      "type": "string"
    },
    "repo_url": {
      "description": "GitHub repository URL (e.g., https://github.com/user/repo)",
      "type": "string"
    },
    "use_cache": {
      "default": true,
      "description": "Enable LLM response caching",
      "type": "boolean"
    }
  },
  "required": [
    "repo_url",
    "llm_provider",
    "api_key"
  ],
  "type": "object"
}

PocketFlow MCP Server

analyze_github_repository

Instructions

Input Schema

Input Schema (JSON Schema)

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