Skill

Document architectural decisions and code rationale

A skill that guides AI assistants to document architectural decisions, API rationale, and code context using ADRs and inline comments that explain why, not

Works with postgresqlmongodbmysqlsqliteprisma

83
Spark score
out of 100
Updated 22 days ago
Version 0.6.3

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Why it matters

Capture the why behind technical decisions through Architecture Decision Records (ADRs) and inline documentation, preserving context about trade-offs, alternatives considered, and constraints that led to implementation choices for future developers and AI agents.

Outcomes

What it gets done

01

Write ADRs for significant architectural decisions like framework selection, database choice, or API design with alternatives considered and consequences

02

Add inline comments explaining non-obvious intent, known gotchas, and critical ordering requirements rather than restating code

03

Document public APIs with TypeScript JSDoc or OpenAPI specs including parameters, return types, error conditions, and usage examples

04

Maintain project READMEs with quick start instructions, command references, architecture overviews, and links to detailed decision records

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-documentation-and-adrs | bash

Overview

Documentation and ADRs

This skill teaches AI assistants to create high-value documentation that captures the *why* behind technical decisions - the context, constraints, and trade-offs that led to choosing one approach over another. It focuses on Architecture Decision Records (ADRs) for significant choices and inline comments that explain non-obvious intent, not code that's already self-explanatory. Use this skill when making significant architectural decisions (choosing frameworks, databases, API architectures), designing data models, selecting authentication strategies, adding or changing public APIs, or shipping features that change user-facing behavior. It's essential when onboarding new team members or agents, or when you find yourself explaining the same technical decision 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. Avoid TODO comments for things you should just

What it does

This skill teaches AI assistants to create high-value documentation that captures the why behind technical decisions - the context, constraints, and trade-offs that led to choosing one approach over another. It focuses on Architecture Decision Records (ADRs) for significant choices and inline comments that explain non-obvious intent, not code that's already self-explanatory.

When to use - and when NOT to

Use this skill when making significant architectural decisions (choosing frameworks, databases, API architectures), designing data models, selecting authentication strategies, adding or changing public APIs, or shipping features that change user-facing behavior. It's essential when onboarding new team members or agents, or when you find yourself explaining the same technical decision 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. Avoid TODO comments for things you should just do now, and never leave commented-out code.

Inputs and outputs

You provide the context of a technical decision: requirements, constraints, alternatives considered, and the chosen solution. The skill outputs structured ADRs stored in docs/decisions/ with sequential numbering and inline code comments that explain non-obvious intent.

Here's a concrete ADR example:

# 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.

And an inline comment pattern:

// 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;
}

Who it's for

This skill is for development teams working with AI assistants on codebases where architectural context matters - projects with significant technical decisions, public APIs, or multiple contributors (human or agent). It's especially valuable for teams that need to prevent re-debating the same decisions months later, onboard new engineers quickly, or ensure AI agents understand why past choices were made and what constraints apply. The ADR lifecycle (PROPOSED → ACCEPTED → SUPERSEDED or DEPRECATED) ensures historical context is never lost, even as decisions evolve.

Source README

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

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)
  • 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.

### [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

Limitations

  • Use this skill only when the task clearly matches its upstream source and local project context.
  • Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
  • Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

FAQ

Common questions

Discussion

Questions & comments · 0

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