Fetches code-documentation from skillcreatorai/ai-agent-skills and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/code-documentation
Restart Cursor to activate code-documentation. Access via /code-documentation in your agent's command palette.
⚠
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
# Project NameBrief description of what this project does.
## Quick Start\`\`\`bash
npm install
npm run dev
\`\`\`
## InstallationDetailed installation instructions...
## Usage\`\`\`typescript
import { something } from 'project';
// Example usage
const result = something.doThing();
\`\`\`
## API Reference### `functionName(param: Type): ReturnType`Description of what the function does.
**Parameters:**-`param` - Description of parameter
**Returns:** Description of return value
**Example:**\`\`\`typescript
const result = functionName('value');
\`\`\`
## Configuration| Option | Type | Default | Description ||--------|------|---------|-------------||`option1`|`string`|`'default'`| What it does |## ContributingHow to contribute...
## LicenseMIT
API Documentation
JSDoc/TSDoc Style
/**
* Creates a new user account.
*
* @param userData - The user data for account creation
* @param options - Optional configuration
* @returns The created user object
* @throws {ValidationError} If email is invalid
* @example
* ```ts
* const user = await createUser({
* email: '[email protected]',
* name: 'John'
* });
* ```
*/asyncfunctioncreateUser( userData: UserInput, options?: CreateOptions
):Promise<User>{// Implementation}/**
* Configuration options for the API client.
*/interfaceClientConfig{/** The API base URL */ baseUrl:string;/** Request timeout in milliseconds @default 5000 */ timeout?:number;/** Custom headers to include in requests */ headers?: Record<string,string>;}
OpenAPI/Swagger
openapi: 3.0.0
info:title: My API
version: 1.0.0
paths:/users:post:summary: Create a user
description: Creates a new user account
requestBody:required:truecontent:application/json:schema:$ref:'#/components/schemas/UserInput'responses:'201':description: User created successfully
content:application/json:schema:$ref:'#/components/schemas/User''400':description: Invalid input
components:schemas:UserInput:type: object
required:- email
- name
properties:email:type: string
format: email
name:type: string
User:type: object
properties:id:type: string
email:type: string
name:type: string
createdAt:type: string
format: date-time
Inline Comments
When to Comment
// GOOD: Explain WHY, not WHAT// Use binary search because the list is always sorted and// can contain millions of items - O(log n) vs O(n)const index =binarySearch(items, target);// GOOD: Explain complex business logic// Users get 20% discount if they've been members for 2+ years// AND have made 10+ purchases (per marketing team decision Q4 2024)if(user.memberYears >=2&& user.purchaseCount >=10){applyDiscount(0.2);}// GOOD: Document workarounds// HACK: Safari doesn't support this API, fallback to polling// TODO: Remove when Safari adds support (tracking: webkit.org/b/12345)if(!window.IntersectionObserver){startPolling();}
When NOT to Comment
// BAD: Stating the obvious// Increment counter by 1counter++;// BAD: Explaining clear code// Check if user is adminif(user.role ==='admin'){...}// BAD: Outdated comments (worse than no comment)// Returns the user's full name <-- Actually returns email now!functiongetUserIdentifier(user){return user.email;}
Architecture Documentation
ADR (Architecture Decision Record)
# ADR-001: Use PostgreSQL for Primary Database## StatusAccepted
## ContextWe need a database for storing user data and transactions.
Options considered: PostgreSQL, MySQL, MongoDB, DynamoDB.
## DecisionUse PostgreSQL with Supabase hosting.
## Rationale- Strong ACID compliance needed for financial data
- Team has PostgreSQL experience
- Supabase provides auth and realtime features
- pgvector extension for future AI features
## Consequences- Need to manage schema migrations
- May need read replicas for scale
- Team needs to learn Supabase-specific features
Component Documentation
## Authentication Module### OverviewHandles user authentication using JWT tokens with refresh rotation.
### Flow1. User submits credentials to `/auth/login`
Implementation Guide
Prerequisites
›Claude Desktop or compatible AI client with skill support
›Clear understanding of task or problem to solve
›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
1Install skill using provided installation command
2Test with simple use case relevant to your work
3Evaluate output quality and relevance
4Iterate on prompts to improve results
5Integrate into regular workflow if valuable
Common Pitfalls
⚠Expecting perfect results without iteration
⚠Not providing enough context in prompts
⚠Using skill for tasks outside its intended scope
⚠Accepting outputs without review and validation
Best Practices
✓ Do
+Start with clear, specific prompts
+Provide relevant context and constraints
+Review and refine all outputs before using
+Iterate to improve output quality
+Document successful prompt patterns
✗ Don't
−Don't use without understanding skill limitations
−Don't skip validation of outputs
−Don't share sensitive information in prompts
−Don't expect skill to replace human judgment
💡 Pro Tips
★Be specific about desired format and style
★Ask for multiple options to choose from
★Request explanations to understand reasoning
★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
1Familiarize yourself with skill capabilities and limitations
2Start with low-risk, non-critical tasks
3Progress to more complex and valuable use cases
4Build expertise through regular use and experimentation
