---
description: Create, update, and manage Architecture Decision Records (ADRs) that capture significant technical decisions — context, options, chosen approach, consequences. Five template variants (MADR, Nygard, Y-statement, lightweight, RFC). Covers ADR lifecycle (proposed → accepted → deprecated / superseded), review process, and adr-tools automation. Use when documenting an architectural choice, reviewing past decisions, or establishing a decision process. Part of the architecture suite (arch-design / arch-decide / arch-document / arch-evaluate + c4-analyze / c4-diagram for notation-specific diagramming).
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---

# Architecture Decision Records

Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions.

## When to Use This Skill

- Making significant architectural decisions
- Documenting technology choices
- Recording design trade-offs
- Onboarding new team members
- Reviewing historical decisions
- Establishing decision-making processes

## Core Concepts

### 1. What is an ADR?

An Architecture Decision Record captures:

- **Context**: Why we needed to make a decision
- **Decision**: What we decided
- **Consequences**: What happens as a result

### 2. When to Write an ADR

| Write ADR                  | Skip ADR               |
| -------------------------- | ---------------------- |
| New framework adoption     | Minor version upgrades |
| Database technology choice | Bug fixes              |
| API design patterns        | Implementation details |
| Security architecture      | Routine maintenance    |
| Integration patterns       | Configuration changes  |

### 3. ADR Lifecycle

```
Proposed → Accepted → Deprecated → Superseded
              ↓
           Rejected
```

## Templates

### Template 1: Standard ADR (MADR Format)

```markdown
# ADR-0001: Use PostgreSQL as Primary Database

## Status

Accepted

## Context

We need to select a primary database for our new e-commerce platform. The system
will handle:

- ~10,000 concurrent users
- Complex product catalog with hierarchical categories
- Transaction processing for orders and payments
- Full-text search for products
- Geospatial queries for store locator

The team has experience with MySQL, PostgreSQL, and MongoDB. We need ACID
compliance for financial transactions.

## Decision Drivers

- **Must have ACID compliance** for payment processing
- **Must support complex queries** for reporting
- **Should support full-text search** to reduce infrastructure complexity
- **Should have good JSON support** for flexible product attributes
- **Team familiarity** reduces onboarding time

## Considered Options

### Option 1: PostgreSQL

- **Pros**: ACID compliant, excellent JSON support (JSONB), built-in full-text
  search, PostGIS for geospatial, team has experience
- **Cons**: Slightly more complex replication setup than MySQL

### Option 2: MySQL

- **Pros**: Very familiar to team, simple replication, large community
- **Cons**: Weaker JSON support, no built-in full-text search (need
  Elasticsearch), no geospatial without extensions

### Option 3: MongoDB

- **Pros**: Flexible schema, native JSON, horizontal scaling
- **Cons**: As of the evaluation in 2024-01, multi-document transactions
  carried constraints we wanted to avoid (see vendor docs cited below);
  team has limited experience, requires schema design discipline

## Decision

We will use **PostgreSQL 15** as our primary database.

## Rationale

PostgreSQL provides the best balance of:

1. **ACID compliance** essential for e-commerce transactions
2. **Built-in capabilities** (full-text search, JSONB, PostGIS) reduce
   infrastructure complexity
3. **Team familiarity** with SQL databases reduces learning curve
4. **Mature ecosystem** with excellent tooling and community support

The slight complexity in replication is outweighed by the reduction in
additional services (no separate Elasticsearch needed).

## Consequences

### Positive

- Single database handles transactions, search, and geospatial queries
- Reduced operational complexity (fewer services to manage)
- Strong consistency guarantees for financial data
- Team can leverage existing SQL expertise

### Negative

- Need to learn PostgreSQL-specific features (JSONB, full-text search syntax)
- Vertical scaling limits may require read replicas sooner
- Some team members need PostgreSQL-specific training

### Risks

- Full-text search may not scale as well as dedicated search engines
- Mitigation: Design for potential Elasticsearch addition if needed

## Implementation Notes

- Use JSONB for flexible product attributes
- Implement connection pooling with PgBouncer
- Set up streaming replication for read replicas
- Use pg_trgm extension for fuzzy search

## Related Decisions

- ADR-0002: Caching Strategy (Redis) - complements database choice
- ADR-0005: Search Architecture - may supersede if Elasticsearch needed

## References

- [PostgreSQL JSON Documentation](https://www.postgresql.org/docs/current/datatype-json.html)
- [PostgreSQL Full Text Search](https://www.postgresql.org/docs/current/textsearch.html)
- [MongoDB Transactions](https://www.mongodb.com/docs/manual/core/transactions/) — backs the multi-document-transaction note in Option 3 (checked 2024-01)
- Internal: Performance benchmarks in `/docs/benchmarks/database-comparison.md`
```

### Template 2: Lightweight ADR

```markdown
# ADR-0012: Adopt TypeScript for Frontend Development

**Status**: Accepted
**Date**: 2024-01-15
**Deciders**: @alice, @bob, @charlie

## Context

Our React codebase has grown to 50+ components with increasing bug reports
related to prop type mismatches and undefined errors. PropTypes provide
runtime-only checking.

## Decision

Adopt TypeScript for all new frontend code. Migrate existing code incrementally.

## Consequences

**Good**: Catch type errors at compile time, better IDE support, self-documenting
code.

**Bad**: Learning curve for team, initial slowdown, build complexity increase.

**Mitigations**: TypeScript training sessions, allow gradual adoption with
`allowJs: true`.
```

### Template 3: Y-Statement Format

```markdown
# ADR-0015: API Gateway Selection

In the context of **building a microservices architecture**,
facing **the need for centralized API management, authentication, and rate limiting**,
we decided for **Kong Gateway**
and against **AWS API Gateway and custom Nginx solution**,
to achieve **vendor independence, plugin extensibility, and team familiarity with Lua**,
accepting that **we need to manage Kong infrastructure ourselves**.
```

### Template 4: ADR for Deprecation

```markdown
# ADR-0020: Deprecate MongoDB in Favor of PostgreSQL

## Status

Accepted (Supersedes ADR-0003)

## Context

ADR-0003 (2021) chose MongoDB for user profile storage due to schema flexibility
needs. Since then:

- MongoDB's multi-document transactions remain problematic for our use case
- Our schema has stabilized and rarely changes
- We now have PostgreSQL expertise from other services
- Maintaining two databases increases operational burden

## Decision

Deprecate MongoDB and migrate user profiles to PostgreSQL.

## Migration Plan

1. **Phase 1** (Week 1-2): Create PostgreSQL schema, dual-write enabled
2. **Phase 2** (Week 3-4): Backfill historical data, validate consistency
3. **Phase 3** (Week 5): Switch reads to PostgreSQL, monitor
4. **Phase 4** (Week 6): Remove MongoDB writes, decommission

## Consequences

### Positive

- Single database technology reduces operational complexity
- ACID transactions for user data
- Team can focus PostgreSQL expertise

### Negative

- Migration effort (~4 weeks)
- Risk of data issues during migration
- Lose some schema flexibility

## Lessons Learned

Document from ADR-0003 experience:

- Schema flexibility benefits were overestimated
- Operational cost of multiple databases was underestimated
- Consider long-term maintenance in technology decisions
```

### Template 5: Request for Comments (RFC) Style

```markdown
# RFC-0025: Adopt Event Sourcing for Order Management

## Summary

Propose adopting event sourcing pattern for the order management domain to
improve auditability, enable temporal queries, and support business analytics.

## Motivation

Current challenges:

1. Audit requirements need complete order history
2. "What was the order state at time X?" queries are impossible
3. Analytics team needs event stream for real-time dashboards
4. Order state reconstruction for customer support is manual

## Detailed Design

### Event Store

```
OrderCreated { orderId, customerId, items[], timestamp }
OrderItemAdded { orderId, item, timestamp }
OrderItemRemoved { orderId, itemId, timestamp }
PaymentReceived { orderId, amount, paymentId, timestamp }
OrderShipped { orderId, trackingNumber, timestamp }
```

### Projections

- **CurrentOrderState**: Materialized view for queries
- **OrderHistory**: Complete timeline for audit
- **DailyOrderMetrics**: Analytics aggregation

### Technology

- Event Store: EventStoreDB (purpose-built, handles projections)
- Alternative considered: Kafka + custom projection service

## Drawbacks

- Learning curve for team
- Increased complexity vs. CRUD
- Need to design events carefully (immutable once stored)
- Storage growth (events never deleted)

## Alternatives

1. **Audit tables**: Simpler but doesn't enable temporal queries
2. **CDC from existing DB**: Complex, doesn't change data model
3. **Hybrid**: Event source only for order state changes

## Unresolved Questions

- [ ] Event schema versioning strategy
- [ ] Retention policy for events
- [ ] Snapshot frequency for performance

## Implementation Plan

1. Prototype with single order type (2 weeks)
2. Team training on event sourcing (1 week)
3. Full implementation and migration (4 weeks)
4. Monitoring and optimization (ongoing)

## References

- [Event Sourcing by Martin Fowler](https://martinfowler.com/eaaDev/EventSourcing.html)
- [EventStoreDB Documentation](https://www.eventstore.com/docs)
```

## ADR Management

### Directory Structure

```
docs/
├── adr/
│   ├── README.md           # Index and guidelines
│   ├── template.md         # Team's ADR template
│   ├── 0001-use-postgresql.md
│   ├── 0002-caching-strategy.md
│   ├── 0003-mongodb-user-profiles.md  # [DEPRECATED]
│   └── 0020-deprecate-mongodb.md      # Supersedes 0003
```

### ADR Index (README.md)

```markdown
# Architecture Decision Records

This directory contains Architecture Decision Records (ADRs) for [Project Name].

## Index

| ADR                                   | Title                              | Status     | Date       |
| ------------------------------------- | ---------------------------------- | ---------- | ---------- |
| [0001](0001-use-postgresql.md)        | Use PostgreSQL as Primary Database | Accepted   | 2024-01-10 |
| [0002](0002-caching-strategy.md)      | Caching Strategy with Redis        | Accepted   | 2024-01-12 |
| [0003](0003-mongodb-user-profiles.md) | MongoDB for User Profiles          | Deprecated | 2023-06-15 |
| [0020](0020-deprecate-mongodb.md)     | Deprecate MongoDB                  | Accepted   | 2024-01-15 |

## Creating a New ADR

1. Copy `template.md` to `NNNN-title-with-dashes.md`
2. Fill in the template
3. Submit PR for review
4. Update this index after approval

## ADR Status

These five are the canonical status set. Use exactly these labels — no synonyms (no "Decided", "Not Accepted", "Active"):

- **Proposed**: Under discussion
- **Accepted**: Decision made, implementing
- **Rejected**: Considered but not adopted
- **Deprecated**: No longer relevant
- **Superseded**: Replaced by another ADR (link forward to the replacement)
```

### Automation (adr-tools)

```bash
# Install adr-tools
brew install adr-tools

# Initialize ADR directory
adr init docs/adr

# Create new ADR
adr new "Use PostgreSQL as Primary Database"

# Supersede an ADR
adr new -s 3 "Deprecate MongoDB in Favor of PostgreSQL"

# Generate table of contents
adr generate toc > docs/adr/README.md

# Link related ADRs
adr link 2 "Complements" 1 "Is complemented by"
```

## Review Process

```markdown
## ADR Review Checklist

### Before Submission

- [ ] Context clearly explains the problem
- [ ] All viable options considered
- [ ] Pros/cons balanced and honest
- [ ] Consequences (positive and negative) documented
- [ ] Related ADRs linked

### During Review

- [ ] At least 2 senior engineers reviewed
- [ ] Affected teams consulted
- [ ] Security implications considered
- [ ] Cost implications documented
- [ ] Reversibility assessed

### After Acceptance

- [ ] ADR index updated
- [ ] Team notified
- [ ] Implementation tickets created
- [ ] Related documentation updated
```

## Best Practices

### Do's

- **Write ADRs early** - Before implementation starts
- **Keep them short** - 1-2 pages maximum
- **Be honest about trade-offs** - Include real cons
- **Cite, don't assert** - Every concrete technical claim about a tool, version, or platform (a missing feature, a benchmark number, a limit) carries a reference: a link, a doc, a version, or a "checked YYYY-MM" date. Capabilities change between releases, so an unsourced "X can't do Y" reads as timeless fact and rots. Scope claims to the date and version they were true for, or replace the specific with a domain-neutral placeholder.
- **Link related decisions** - Build decision graph
- **Update status** - Deprecate when superseded

### Don'ts

- **Don't change accepted ADRs** - An accepted ADR's body is immutable. The only edits allowed after acceptance are to status/link metadata: flipping the Status line (to Deprecated or Superseded) and adding a forward link to the ADR that replaces it. When a decision changes, write a NEW ADR that supersedes the old one — set the new ADR's status to `Accepted (Supersedes ADR-NNNN)` and the old ADR's status to `Superseded by ADR-MMMM`. The old ADR stays in the directory as the historical record; never delete or rewrite it.
- **Don't skip context** - Future readers need background
- **Don't hide failures** - Rejected decisions are valuable
- **Don't be vague** - Specific decisions, specific consequences
- **Don't forget implementation** - ADR without action is waste

---

## Attribution

Forked from [wshobson/agents](https://github.com/wshobson/agents) — MIT licensed.
See `LICENSE` in this directory for the original copyright and terms.

## Content scope

Output this skill produces that gets committed or shared with the team must follow the *Content scope for public artifacts* rule in [`commits.md`](../claude-rules/commits.md): no local paths, no private repo names, no personal tooling references.