Generate Comprehensive Code Documentation
AI skill for generating code documentation - JSDoc/docstring comments, REST API docs, and structured README files.
Why it matters
Automate the creation of high-quality, maintainable code documentation for various programming languages and API specifications. Ensure code clarity, consistency, and accuracy for developers and end-users.
Outcomes
What it gets done
Generate inline code comments (JSDoc, Python docstrings).
Create API documentation templates (REST).
Structure README files with best practices.
Maintain documentation synchronization with code changes.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-code-documentation-generator | bash Overview
Code Documentation Generator Agent
Generates code documentation - JSDoc/docstring inline comments, REST API endpoint documentation, and structured README files. Use when writing documentation for code, APIs, or projects that will be used or maintained by other developers.
What it does
This skill provides expertise in generating code documentation, with deep knowledge of documentation standards, best practices, and tooling across programming languages, producing clear, comprehensive, maintainable documentation for both developers and end users. Core documentation principles emphasize clarity over sophistication (explaining not just what code does but why it exists and how it fits the system), progressive disclosure (structuring from high-level concepts down to implementation details), consistency (uniform formatting, terminology, and structure), accuracy (documentation kept in sync with code changes), and accessibility (writing for a diverse audience of junior developers, maintainers, and API consumers).
Code comment standards follow language-specific conventions: JavaScript/TypeScript uses JSDoc (parameter types and descriptions, return type, thrown errors, and a runnable example) and Python uses docstrings (a summary, detailed Args/Returns/Raises sections with types, a runnable doctest-style example, and notes on side effects like whether the function mutates its input). API documentation templates structure REST endpoint docs with a clear method/path, authentication requirements, a request body schema documented as a field table (name, type, required, description), and both success and error response examples with realistic status codes and payloads.
README documentation structure follows a consistent template: a brief compelling project description, build/license badges, a features list, a quick-start section with installation and basic usage code, an installation section covering prerequisites and development setup steps (clone, install, run), and further sections for configuration, usage examples, and contribution guidelines. Throughout, documentation examples are written to be directly runnable and copy-pasteable, matching the actual behavior of the code they describe.
When to use - and when NOT to
Use this skill when writing inline code documentation (JSDoc/docstrings), API endpoint documentation, or project README files that need to be accurate, runnable, and consistently structured. It is well suited to codebases and APIs that will be used or maintained by developers beyond the original author. It is not meant for throwaway scripts with no reuse or maintenance need, where full documentation overhead isn't worth the effort.
Inputs and outputs
Input: the function, API endpoint, or project to document.
Output: inline code comments (JSDoc/docstrings), API endpoint documentation, or a structured README, each following language- or format-specific conventions. Example JSDoc comment:
/**
* Calculates the compound interest for a given principal amount
* @param {number} principal - The initial amount of money
* @param {number} rate - The annual interest rate (as decimal)
* @returns {number} The final amount after compound interest
* @throws {Error} When principal, rate, or time are negative
*/
function calculateCompoundInterest(principal, rate, time, compoundFreq = 1) { }
Integrations
Produces documentation in standard formats compatible with JSDoc, Python docstring, and Markdown tooling; it does not connect to a specific documentation generation platform itself.
Who it's for
Developers documenting functions, APIs, or projects for other developers to maintain or consume, and teams that need consistent, runnable documentation examples rather than sparse or outdated comments.
FAQ
Common questions
Discussion
Questions & comments ยท 0
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