documentation-and-adrs

Documentation and ADRs

Overview

Document decisions, not just code. The most valuable documentation captures the why — the context, constraints, and trade-offs that led to a decision. Code shows what was built; documentation explains why it was built this way and what alternatives were considered. This context is essential for future humans and agents working in the codebase.

When to Use

• Making a significant architectural decision
• Choosing between competing approaches
• Adding or changing a public API
• Shipping a feature that changes user-facing behavior
• Onboarding new team members (or agents) to the project
• When you find yourself explaining the same thing repeatedly

When NOT to use: Don't document obvious code. Don't add comments that restate what the code already says. Don't write docs for throwaway prototypes.

Architecture Decision Records (ADRs)

ADRs capture the reasoning behind significant technical decisions. They're the highest-value documentation you can write.

When to Write an ADR

• Choosing a framework, library, or major dependency
• Designing a data model or database schema
• Selecting an authentication strategy
• Deciding on an API architecture (REST vs. GraphQL vs. tRPC)
• Choosing between build tools, hosting platforms, or infrastructure
• Any decision that would be expensive to reverse

Match the existing convention first

Before creating an ADR, inspect the available repository context for an established convention — existing ADRs, project instructions, and ADR-related configuration or tooling (e.g. an .adr-dir file). An established convention overrides the defaults below. Match:

• Location and format — e.g. docs/adr/*.md, Documentation/Decisions/*.rst, a MADR layout, or an adr-tools setup. Match the existing directory, file extension, and markup (Markdown vs reStructuredText).
• Numbering and naming — continue the existing sequence and filename pattern (ADR-004-Title.rst, 0004-title.md, …); don't restart at 001 or introduce a second scheme.
• Section headings — reuse the project's heading set rather than imposing this template's.

If the available evidence conflicts, surface the conflict rather than silently introducing another scheme. Only when no convention can be established do you apply the default below.

ADR Template

Store ADRs in docs/decisions/ with sequential numbering (unless the project already uses another location — see above):

# ADR-001: Use PostgreSQL for primary database

## Status
Proposed | Accepted | Superseded by ADR-XXX | Deprecated

## Date
2025-01-15

## Context
We need a primary database for the task management application. Key requirements:
- Relational data model (users, tasks, teams with relationships)
- ACID transactions for task state changes
- Support for full-text search on task content
- Managed hosting available (for small team, limited ops capacity)

## Decision
Use PostgreSQL with Prisma ORM.

## Alternatives Considered

### MongoDB
- Pros: Flexible schema, easy to start with
- Cons: Our data is inherently relational; would need to manage relationships manually
- Rejected: Relational data in a document store leads to complex joins or data duplication

### SQLite
- Pros: Zero configuration, embedded, fast for reads
- Cons: Limited concurrent write support, no managed hosting for production
- Rejected: Not suitable for multi-user web application in production

### MySQL
- Pros: Mature, widely supported
- Cons: PostgreSQL has better JSON support, full-text search, and ecosystem tooling
- Rejected: PostgreSQL is the better fit for our feature requirements

## Consequences
- Prisma provides type-safe database access and migration management
- We can use PostgreSQL's full-text search instead of adding Elasticsearch
- Team needs PostgreSQL knowledge (standard skill, low risk)
- Hosting on managed service (Supabase, Neon, or RDS)

ADR Lifecycle

PROPOSED → ACCEPTED → (SUPERSEDED or DEPRECATED)

• Don't delete old ADRs. They capture historical context.
• When a decision changes, write a new ADR that references and supersedes the old one.

Inline Documentation

When to Comment

Comment the why, not the what:

// BAD: Restates the code
// Increment counter by 1
counter += 1;

// GOOD: Explains non-obvious intent
// Rate limit uses a fixed window that opens on the first request after the
// previous one expires, not on a clock schedule. Known gap: a client can spend
// the full limit just before a reset and again just after (2x in a moment)
if (now - windowStart > WINDOW_SIZE_MS) {
  counter = 0;
  windowStart = now;
}

When NOT to Comment

// Don't comment self-explanatory code
function calculateTotal(items: CartItem[]): number {
  return items.reduce((sum, item) => sum + item.price * item.quantity, 0);
}

// Don't leave TODO comments for things you should just do now
// TODO: add error handling  ← Just add it

// Don't leave commented-out code
// const oldImplementation = () => { ... }  ← Delete it, git has history

Document Known Gotchas

/**
 * IMPORTANT: This function must be called before the first render.
 * If called after hydration, it causes a flash of unstyled content
 * because the theme context isn't available during SSR.
 *
 * See ADR-003 for the full design rationale.
 */
export function initializeTheme(theme: Theme): void {
  // ...
}

API Documentation

For public APIs (REST, GraphQL, library interfaces):

Inline with Types (Preferred for TypeScript)

/**
 * Creates a new task.
 *
 * @param input - Task creation data (title required, description optional)
 * @returns The created task with server-generated ID and timestamps
 * @throws {ValidationError} If title is empty or exceeds 200 characters
 * @throws {AuthenticationError} If the user is not authenticated
 *
 * @example
 * const task = await createTask({ title: 'Buy groceries' });
 * console.log(task.id); // "task_abc123"
 */
export async function createTask(input: CreateTaskInput): Promise<Task> {
  // ...
}

OpenAPI / Swagger for REST APIs

paths:
  /api/tasks:
    post:
      summary: Create a task
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreateTaskInput'
      responses:
        '201':
          description: Task created
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Task'
        '422':
          description: Validation error

README Structure

Every project should have a README that covers:

# Project Name

One-paragraph description of what this project does.

## Quick Start
1. Clone the repo
2. Install dependencies: `npm install`
3. Set up environment: `cp .env.example .env`
4. Run the dev server: `npm run dev`

## Commands
| Command | Description |
|---------|-------------|
| `npm run dev` | Start development server |
| `npm test` | Run tests |
| `npm run build` | Production build |
| `npm run lint` | Run linter |

## Architecture
Brief overview of the project structure and key design decisions.
Link to ADRs for details.

## Contributing
How to contribute, coding standards, PR process.

Changelog Maintenance

For shipped features:

# Changelog

## [1.2.0] - 2025-01-20
### Added
- Task sharing: users can share tasks with team members (#123)
- Email notifications for task assignments (#124)

### Fixed
- Duplicate tasks appearing when rapidly clicking create button (#125)

### Changed
- Task list now loads 50 items per page (was 20) for better UX (#126)

Documentation for Agents

Special consideration for AI agent context:

• CLAUDE.md / rules files — Document project conventions so agents follow them
• Spec files — Keep specs updated so agents build the right thing
• ADRs — Help agents understand why past decisions were made (prevents re-deciding)
• Inline gotchas — Prevent agents from falling into known traps

Prose Review

After checking the technical content, review the prose for the people who will use it. Clearer wording must not change the decision or its limits.

1. Mark the details that must survive the edit: names, numbers and units, commands, paths, links, conditions, trade-offs, and uncertainty. Check them against the available code and decision context; flag anything you cannot substantiate.
2. Replace stock introductions, promotional adjectives, and repeated summaries with the concrete information the reader needs. Do not replace an unsupported claim with an invented example or a stronger guarantee. Keep necessary technical repetition and the project's established terminology.
3. Compare the edited document with the original and its sources. Restore any lost qualifier or caveat, verify command and code examples still work as documented, and explain any unresolved factual question rather than polishing it away.

Common Rationalizations

Red Flags

• Architectural decisions with no written rationale
• Public APIs with no documentation or types
• README that doesn't explain how to run the project
• Commented-out code instead of deletion
• TODO comments that have been there for weeks
• No ADRs in a project with significant architectural choices
• Documentation that restates the code instead of explaining intent

Verification

After documenting:

• [ ] ADRs exist for all significant architectural decisions
• [ ] README covers quick start, commands, and architecture overview
• [ ] API functions have parameter and return type documentation
• [ ] Known gotchas are documented inline where they matter
• [ ] No commented-out code remains
• [ ] Rules files (CLAUDE.md etc.) are current and accurate
• [ ] Prose edits preserve source details, decision trade-offs, and qualifiers without adding unsupported guarantees