Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
git clone https://github.com/addyosmani/agent-skills.git--- name: documentation-and-adrs description: Records decisions and documentation. Use when making architectural decisions, changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase. --- # 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): ```markdown # 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*: ```typescript // 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 ```typescript // 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 ```typescript /** * 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) ```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 ```yaml 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: ```markdown # 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: ```markdown # 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
[{"step":"Identify the decision or change requiring documentation. This could be a new feature, a change to a public API, an architectural shift, or any context that future engineers or agents will need to understand.","action":"Use the prompt template to generate an ADR. Replace [FEATURE/CHANGE] with the specific change or decision, and fill in the placeholders like [PROJECT_NAME], [TEAM_NAME], and [DATE].","tip":"Start with the 'Context' section to clearly articulate the problem or opportunity driving the decision. This ensures the ADR is grounded in real needs."},{"step":"Fill in the 'Decision' section with the chosen solution and the rationale behind it. Be specific about the technology, pattern, or approach selected.","action":"Describe the decision in detail, including any trade-offs considered. If multiple options were evaluated, briefly summarize why the chosen option was selected over alternatives.","tip":"Use bullet points or sub-sections to break down complex decisions into digestible parts. This makes the ADR easier to reference later."},{"step":"Document the 'Consequences' and 'Alternatives Considered' sections. These are critical for future engineers to understand the impact of the decision and why it was made.","action":"List the positive and negative consequences of the decision, as well as the alternatives that were considered and rejected. Include links to relevant resources or discussions.","tip":"Be honest about the drawbacks of the chosen solution. This helps future engineers avoid pitfalls and understand the full context of the decision."},{"step":"Save the ADR in a dedicated directory (e.g., `/docs/adrs/`) in your project repository. Name the file following a consistent naming convention, such as `adr-001-title.md`.","action":"Commit the ADR to version control and ensure it is accessible to the entire team. Update the ADR if the decision is revisited or superseded by a new ADR.","tip":"Use a tool like `adr-tools` (https://github.com/npryce/adr-tools) to automate the creation and management of ADRs. This ensures consistency and makes it easier to reference existing ADRs."},{"step":"Reference the ADR in relevant documentation, code comments, or pull requests. This ensures the context of the decision is easily accessible to anyone working on the codebase.","action":"Link to the ADR in places where the decision is relevant, such as in API documentation, architecture diagrams, or code comments. For example, add a comment like `// See ADR-001 for the rationale behind using Kong Gateway.`","tip":"Use a consistent format for referencing ADRs, such as `// ADR-{number}: {brief description}` in code comments or `See [ADR-{number}](#adr-{number})` in Markdown documentation."}]
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/addyosmani/agent-skills/tree/main/skills/documentation-and-adrsCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Document the architectural decision for [FEATURE/CHANGE]. Include the context, the decision made, the alternatives considered, and the consequences of the decision. Format this as an Architecture Decision Record (ADR) following the Markdown template below. Use [PROJECT_NAME], [TEAM_NAME], and [DATE] as placeholders. --- # [PROJECT_NAME] Architecture Decision Record [ADR_NUMBER] ## Status Proposed | Accepted | Rejected | Deprecated | Superseded ## Context [Provide the context surrounding the decision, including the problem being solved and any relevant background.] ## Decision [Describe the decision made and the rationale behind it.] ## Consequences [Outline the positive and negative consequences of this decision.] ## Alternatives Considered [List the alternatives that were considered and why they were not chosen.] ## References [Link to any relevant documents, discussions, or resources.] --- Date: [DATE] Team: [TEAM_NAME]
```markdown --- # Acme Corp API Gateway Architecture Decision Record ADR-001 ## Status Accepted ## Context Acme Corp is migrating its monolithic backend to a microservices architecture to improve scalability and maintainability. The API Gateway is a critical component that will route requests to the appropriate microservices. The team needs to decide on the technology and architecture pattern for the API Gateway to ensure high availability, low latency, and ease of maintenance. ## Decision We will use **Kong Gateway** as our API Gateway solution. Kong was chosen for its open-source nature, extensive plugin ecosystem, and proven scalability. It supports dynamic routing, rate limiting, and authentication, which align with our requirements. Additionally, Kong’s compatibility with Kubernetes (via the Kong Ingress Controller) will simplify our deployment and management processes. ## Consequences **Positive:** - Kong’s plugin ecosystem allows us to easily add features like rate limiting, request/response transformations, and authentication without custom development. - Kong’s performance benchmarks indicate it can handle high throughput with minimal latency, which is critical for our user-facing APIs. - The open-source version is free, reducing licensing costs compared to commercial alternatives like AWS API Gateway or Apigee. **Negative:** - Kong requires additional infrastructure (e.g., a database for its configuration) compared to serverless options like AWS Lambda. - The team will need to invest time in learning Kong’s configuration and management tools. ## Alternatives Considered 1. **AWS API Gateway:** While fully managed, it locks us into AWS and may incur higher costs at scale. Additionally, it lacks some advanced features available in Kong’s plugin ecosystem. 2. **Nginx:** A lightweight option, but it lacks built-in support for advanced API gateway features like rate limiting and authentication out of the box. 3. **Traefik:** A modern, cloud-native gateway, but it has a smaller community and fewer plugins compared to Kong. ## References - [Kong Gateway Documentation](https://docs.konghq.com/) - [Kong vs. AWS API Gateway Comparison](https://www.getambassador.io/resources/kong-vs-aws-api-gateway/) - [Acme Corp Microservices Architecture RFC](https://internal.acmecorp.com/rfcs/microservices-architecture) --- Date: 2024-05-20 Team: Platform Engineering
skills-collection
Take a free 3-minute scan and get personalized AI skill recommendations.
Take free scan