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.
For coding-related documentation or ADRs, load engineering-principles before
this skill so recorded decisions preserve the local standards for architecture,
testing, validation, tooling, and simplicity.
Text And Docs Style
When writing any kind of text - message for a user, a prompt for subagent, a doc - prefer rich markdown structure with diagrams, maps, compact tables, and short sections over long flat tables or deeply nested bullet. Structure should help both humans and AI agents understand how ideas connect.
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
ADR Template
Store ADRs in docs/decisions/ with sequential numbering:
# ADR-001: Use PostgreSQL for primary database
## Status
Accepted | Superseded by ADR-XXX | Deprecated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)
- Delete old/deprecated docs. If they have context that is still important, extract it into new docs.
- When a decision changes, write a new ADR that references and supersedes the old one.
Inline Documentation
When to Comment
Defer to the canonical commenting policy in engineering-principles. Inline
documentation preserves intent rather than narrating syntax: business rules and
invariants require explanation, while obvious code does not.
// BAD: Restates the code
// Increment counter by 1
counter += 1;
// GOOD: Explains non-obvious intent
// Rate limit uses a sliding window — reset counter at window boundary,
// not on a fixed schedule, to prevent burst attacks at window edges
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):
In-Process TypeScript Interfaces
TypeScript types effectively document in-process programmable interfaces. For internal module boundaries, inline JSDoc or typed interfaces are sufficient.
/**
* 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> {
// ...
}
External Transport Contracts
Plain TypeScript types alone are insufficient for external HTTP transports because they are erased at runtime. For REST or GraphQL APIs:
- Choose one authoritative source of truth following the roadmap's contract
selection strategy:
- Closely coupled private TypeScript systems: shared transport runtime schemas (e.g., Zod, Valibot) with inferred types — not domain or persistence models.
- Public, cross-repository, or cross-language APIs: a complete OpenAPI document as the authoritative contract.
- Documentation, generated clients, and test-server inputs are derived artifacts, not independent sources of truth.
- Ensure OpenAPI documents are generated and aligned with endpoint behavior, not maintained as a second manual document.
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.
Documentation for Agents
Special consideration for AI agent context:
- AGENTS.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
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "The code is self-documenting" | Code shows what. It doesn't show why, what alternatives were rejected, or what constraints apply. |
| "We'll write docs when the API stabilizes" | APIs stabilize faster when you document them. The doc is the first test of the design. |
| "Nobody reads docs" | Agents do. Future engineers do. Your 3-months-later self does. |
| "ADRs are overhead" | A 10-minute ADR prevents a 2-hour debate about the same decision six months later. |
| "Comments get outdated" | Comments on why are stable. Comments on what get outdated — that's why you only write the former. |
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
- 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