| name | documentation |
| description | Technical writing, API docs, and documentation best practices |
| domain | software-engineering |
| version | 1.0.0 |
| tags | documentation, technical-writing, api-docs, adr, readme, runbooks |
| triggers | [object Object] |
Documentation
Overview
Documentation as a first-class engineering artifact. Good docs reduce onboarding time, support tickets, and cognitive load.
Documentation Types
| Type | Audience | Purpose | Update Frequency |
|---|---|---|---|
| README | New developers | Quick start | Per major change |
| API Docs | API consumers | Reference | Per API change |
| Architecture | Team | Design decisions | Per design change |
| Runbooks | Operations | Incident response | Per incident |
| Tutorials | Users | Learning | Periodically |
README Best Practices
Structure
# Project Name
> One-line description of what this project does.
[](link)
[](link)
[](link)
## Features
- Feature 1: Brief description
- Feature 2: Brief description
- Feature 3: Brief description
## Quick Start
```bash
# Install
npm install my-project
# Configure
export API_KEY=your-key
# Run
npx my-project start
Installation
Prerequisites
- Node.js 18+
- PostgreSQL 15+
Steps
- Clone the repository
- Install dependencies:
npm install - Copy
.env.exampleto.env - Run migrations:
npm run db:migrate - Start the server:
npm start
Usage
Basic Example
import { Client } from 'my-project';
const client = new Client({ apiKey: 'xxx' });
const result = await client.doSomething();
Advanced Configuration
[Link to detailed docs]
API Reference
[Link to API docs]
Contributing
See CONTRIBUTING.md
License
MIT - see LICENSE
---
## API Documentation
### OpenAPI/Swagger
```yaml
openapi: 3.0.3
info:
title: User API
description: |
API for managing users.
## Authentication
All endpoints require Bearer token authentication.
## Rate Limiting
- 100 requests per minute per API key
- 429 response when exceeded
version: 1.0.0
servers:
- url: https://api.example.com/v1
description: Production
- url: https://staging-api.example.com/v1
description: Staging
paths:
/users:
get:
summary: List users
description: Returns a paginated list of users.
operationId: listUsers
tags:
- Users
parameters:
- name: limit
in: query
description: Maximum number of users to return
schema:
type: integer
default: 20
maximum: 100
- name: cursor
in: query
description: Pagination cursor from previous response
schema:
type: string
responses:
'200':
description: Successful response
content:
application/json:
schema:
$ref: '#/components/schemas/UserList'
example:
data:
- id: "usr_123"
email: "user@example.com"
name: "John Doe"
meta:
hasMore: true
nextCursor: "eyJpZCI6MTIzfQ"
'401':
$ref: '#/components/responses/Unauthorized'
components:
schemas:
User:
type: object
required:
- id
- email
properties:
id:
type: string
description: Unique identifier
example: "usr_123"
email:
type: string
format: email
description: User's email address
name:
type: string
description: User's display name
responses:
Unauthorized:
description: Authentication required
content:
application/json:
schema:
type: object
properties:
error:
type: string
example: "Invalid or missing API key"
Code Examples in Docs
## Creating a User
### Request
```bash
curl -X POST https://api.example.com/v1/users \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"email": "user@example.com",
"name": "John Doe"
}'
Response
{
"id": "usr_123",
"email": "user@example.com",
"name": "John Doe",
"createdAt": "2024-01-15T10:30:00Z"
}
Error Response
{
"error": {
"code": "validation_error",
"message": "Invalid email format",
"field": "email"
}
}
---
## Architecture Decision Records (ADR)
### Template
```markdown
# ADR-001: Use PostgreSQL for Primary Database
## Status
Accepted
## Context
We need to choose a primary database for our application.
Requirements:
- ACID transactions
- Complex queries with joins
- Proven reliability at scale
- Good ecosystem and tooling
## Decision
We will use PostgreSQL as our primary database.
## Alternatives Considered
### MySQL
- Pros: Widely used, good performance
- Cons: Less feature-rich, weaker JSON support
### MongoDB
- Pros: Flexible schema, easy horizontal scaling
- Cons: No ACID transactions across documents, eventual consistency
### CockroachDB
- Pros: Distributed, PostgreSQL-compatible
- Cons: Higher operational complexity, newer technology
## Consequences
### Positive
- Strong consistency guarantees
- Rich query capabilities (CTEs, window functions)
- Excellent JSON support for semi-structured data
- Large community and ecosystem
### Negative
- Vertical scaling limits
- Need to manage read replicas for high read loads
- Schema migrations require careful planning
### Risks
- May need sharding solution if we exceed single-node capacity
- Team needs PostgreSQL expertise
## References
- [PostgreSQL Documentation](https://www.postgresql.org/docs/)
- [Internal benchmark results](link)
ADR Index
# Architecture Decision Records
| ID | Title | Status | Date |
|----|-------|--------|------|
| [ADR-001](adr-001.md) | Use PostgreSQL | Accepted | 2024-01-01 |
| [ADR-002](adr-002.md) | JWT Authentication | Accepted | 2024-01-05 |
| [ADR-003](adr-003.md) | Microservices Split | Proposed | 2024-01-10 |
| [ADR-004](adr-004.md) | GraphQL vs REST | Superseded by ADR-006 | 2024-01-15 |
Code Documentation
JSDoc / TSDoc
/**
* Calculates the total price including tax and discounts.
*
* @param items - Array of cart items
* @param options - Calculation options
* @returns The calculated price breakdown
*
* @example
* ```typescript
* const result = calculatePrice(
* [{ id: '1', price: 100, quantity: 2 }],
* { taxRate: 0.1, discountCode: 'SAVE10' }
* );
* console.log(result.total); // 198
* ```
*
* @throws {ValidationError} If items array is empty
* @throws {InvalidDiscountError} If discount code is invalid
*
* @see {@link applyDiscount} for discount logic
* @since 2.0.0
*/
function calculatePrice(
items: CartItem[],
options: PriceOptions
): PriceBreakdown {
// Implementation
}
/**
* Represents a user in the system.
*
* @remarks
* Users are created through the signup flow or admin panel.
* Soft deletion is used - check `deletedAt` for active status.
*/
interface User {
/** Unique identifier (UUID v4) */
id: string;
/** Email address (unique, validated format) */
email: string;
/**
* User's display name
* @defaultValue Derived from email if not provided
*/
name?: string;
/** Account creation timestamp */
createdAt: Date;
/** Soft deletion timestamp, null if active */
deletedAt: Date | null;
}
Inline Comments
// ✅ Good: Explains WHY
// Use binary search because items are sorted and list can have 100k+ entries
const index = binarySearch(items, target);
// ✅ Good: Explains non-obvious behavior
// Sleep 100ms to avoid rate limiting from external API
await sleep(100);
// ✅ Good: Documents workaround
// HACK: Safari doesn't support this API, fall back to polyfill
// TODO: Remove when Safari 17 adoption > 90%
const result = window.api?.call() ?? polyfill();
// ❌ Bad: States the obvious
// Loop through users
for (const user of users) {
// ❌ Bad: Outdated comment
// Returns user's full name (actually returns email now)
function getUserIdentifier() {
return user.email;
}
Runbooks
Structure
# Runbook: High Memory Usage Alert
## Overview
This runbook addresses alerts when application memory usage exceeds 80%.
## Prerequisites
- Access to Kubernetes cluster
- Permissions to view pods and logs
- Familiarity with application architecture
## Symptoms
- Alert: `HighMemoryUsage` firing
- Metric: `container_memory_usage_bytes` > 80% of limit
- Possible: OOMKilled pods, slow responses
## Diagnosis
### Step 1: Identify affected pods
```bash
kubectl top pods -n production | sort -k3 -rh | head -10
Step 2: Check for memory leaks
# Get heap dump
kubectl exec -it <pod> -- node --heapsnapshot
kubectl cp <pod>:/app/heapsnapshot.heapsnapshot ./heapsnapshot.heapsnapshot
Step 3: Check recent deployments
kubectl rollout history deployment/api -n production
Mitigation
Immediate (if pods are crashing)
# Scale up to distribute load
kubectl scale deployment/api --replicas=10
# Restart pods (rolling)
kubectl rollout restart deployment/api
If memory leak confirmed
- Identify the leaking code path from heap snapshot
- Prepare hotfix
- Deploy fix following standard process
Resolution
- Memory usage returns below 70%
- No OOMKilled events for 30 minutes
- Alert auto-resolves
Escalation
- L1: On-call engineer
- L2: Platform team (if infrastructure issue)
- L3: Application team lead (if code issue)
Related
- Memory Profiling Guide
- Incident INC-123 - Previous memory leak
---
## Documentation Tools
| Tool | Use Case | Format |
|------|----------|--------|
| Docusaurus | Documentation sites | MDX |
| Swagger UI | API reference | OpenAPI |
| Storybook | Component docs | JSX/TSX |
| MkDocs | Technical docs | Markdown |
| Notion | Team wikis | Rich text |
---
## Related Skills
- [[api-design]] - API documentation
- [[code-quality]] - Self-documenting code
- [[reliability-engineering]] - Runbooks