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addyosmani/documentation-and-adrs

addyosmani

documentation-and-adrs

Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.

NewUpdated Sep 9, 2026

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
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 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):

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

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
  • 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
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Overall Score

88/100

Grade

A

Excellent

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

92

Quality

88

Clarity

87

Completeness

83

Summary

This skill teaches documentation best practices, including writing Architecture Decision Records (ADRs), API documentation, README structure, and inline code comments. It provides templates, conventions, and guidance on when and how to document decisions, with emphasis on capturing the "why" rather than just the "what". The skill is designed to help engineers and AI agents understand project context and design rationale.

Static Analysis Findings

1 finding

Patterns detected by deterministic static analysis before AI scoring. Hover over any finding code for detailed information and remediation guidance.

Credential Exposure
SEC-020Direct .env File Access2x in 1 file

Direct .env file access

SKILL.md.env2x

Detected Capabilities

file read (inspect existing ADRs and conventions)file write (create new ADRs, update README, document APIs)git history inspection (reference historical decisions)documentation generation (produce markdown documents)

Trigger Keywords

Phrases that agents use to match this skill to user intent.

architecture decision recorddocument design decisionapi documentationproject readmeadr templatedecision rationalearchitectural choiceonboard to codebase

Risk Signals

INFO

SEC-020: References .env file in README quick-start instructions ('cp .env.example .env')

SKILL.md | README Structure section
INFO

SEC-020: Mentions .env file access in context of documentation examples

SKILL.md | README Structure section

Use Cases

  • . Recording architectural decisions and their rationale for future team members and AI agents
  • Documenting why a framework, library, or major dependency was chosen
  • Creating API documentation with parameter descriptions and error handling
  • Writing project READMEs that cover quick start, commands, and architecture overview
  • Establishing project-wide documentation conventions through ADRs and rules files
  • Preventing repeated design discussions by capturing decisions with alternatives considered
  • Onboarding new engineers and AI agents to understand codebase design choices

Quality Notes

  • Excellent structure with clear sections, practical examples, and templates ready to use
  • Provides concrete ADR template with realistic examples (PostgreSQL decision) showing good decision documentation
  • Distinguishes when to comment vs. when not to comment, with clear examples of bad and good patterns
  • Includes practical advice on matching existing conventions before imposing new ones, reducing friction in adoption
  • Strong emphasis on documenting the 'why' rather than the 'what' aligns with best practices for human and AI understanding
  • Verification checklist at the end helps teams assess documentation completeness
  • Well-balanced tone between being prescriptive and allowing flexibility based on project context
  • Includes guidance specific to AI agent context, showing awareness of audience needs
  • ADR lifecycle and status options (Accepted, Superseded, Deprecated) are clearly explained with lifecycle diagram
  • Red flags section helps teams identify documentation anti-patterns
Model: claude-haiku-4-5-20251001Analyzed: Sep 9, 2026

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Version History

  1. v2.0

    Contract changed: description

    ✦ AIPrioritizes conformance to existing ADR conventions in the repository before applying default template.

    triggering2026-09-09

    LATEST
  2. v1.0

    2026-05-02

    View This VersionInitial version

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