Skip to main content
Glama

generate_tutorial

Creates a comprehensive tutorial for any initialized codebase, featuring architecture overview, Mermaid diagrams, and a structured learning path to master the project.

Instructions

Generate a comprehensive tutorial/learning guide for a codebase. Creates a "Zero to Hero" tutorial with:

  • Project overview and architecture

  • Mermaid.js dependency diagrams

  • Structured learning path (chapters)

  • Key insights and patterns

Requires init_codebase to be run first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rootPathYesAbsolute path to the codebase root (must have been initialized)
focusTopicNoOptional: Focus the tutorial on a specific topic or area (e.g., 'authentication', 'database')
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries the burden of behavioral disclosure. It discloses the prerequisite and outlines the tutorial's content structure (e.g., Mermaid diagrams, learning path). However, it does not clarify whether the tool writes files, modifies the codebase, or what the exact return format is, leaving some behavioral ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear opening sentence followed by a bulleted list of outputs, and ends with a prerequisite. It is concise and front-loaded, though the bullet list is slightly verbose. There is no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (prerequisite, multiple output types) and no output schema or annotations, the description covers the key purpose and prerequisite but lacks details on return values, error handling, and how focusTopic modifies the output. It is minimally adequate but incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Since schema description coverage is 100%, the baseline for this dimension is 3. The description adds no additional parameter detail beyond the schema; rootPath and focusTopic are not discussed in the description, but the schema already provides adequate descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action (generate a comprehensive tutorial/learning guide) and the resource (codebase). It distinguishes itself from sibling tools init_codebase and search_codebase by focusing on producing a tutorial artifact rather than initializing or searching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states a prerequisite ('Requires init_codebase to be run first'), indicating when it is appropriate to use this tool. It does not explicitly mention alternatives or exclusions, but the prerequisite provides clear usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/skainguyen1412/mcp-codebase'

If you have feedback or need assistance with the MCP directory API, please join our Discord server