documentation-and-adrs

OWNER/REPO · updated May 7, 2026

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$npx skills add https://github.com/addyosmani/agent-skills --skill documentation-and-adrs
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summary

Records decisions and documentation for architectural choices, public APIs, and feature shipping to aid future engineers and agents.

skill.md
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

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Accepted | Superseded by ADR-XXX | Deprecated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.

## 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

RationalizationReality
"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
how to use documentation-and-adrs

How to use documentation-and-adrs on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add documentation-and-adrs
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/addyosmani/agent-skills --skill documentation-and-adrs

The skills CLI fetches documentation-and-adrs from GitHub repository OWNER/REPO and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/documentation-and-adrs

Reload or restart Cursor to activate documentation-and-adrs. Access the skill through slash commands (e.g., /documentation-and-adrs) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.446 reviews
  • Hassan Abebe· Dec 24, 2024

    I recommend documentation-and-adrs for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Hiroshi Abbas· Dec 16, 2024

    Keeps context tight: documentation-and-adrs is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Anika Lopez· Dec 12, 2024

    Registry listing for documentation-and-adrs matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Fatima Rao· Nov 23, 2024

    documentation-and-adrs has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Alexander Chawla· Nov 15, 2024

    Solid pick for teams standardizing on skills: documentation-and-adrs is focused, and the summary matches what you get after install.

  • Anaya Sanchez· Nov 7, 2024

    documentation-and-adrs is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Rahul Santra· Nov 3, 2024

    documentation-and-adrs fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Neel Okafor· Nov 3, 2024

    documentation-and-adrs reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Sakura Farah· Oct 26, 2024

    Solid pick for teams standardizing on skills: documentation-and-adrs is focused, and the summary matches what you get after install.

  • Pratham Ware· Oct 22, 2024

    documentation-and-adrs has been reliable in day-to-day use. Documentation quality is above average for community skills.

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