---

name: adr-writing description: Write Architectural Decision Records following MADR template. Applies Definition of Done criteria, marks gaps for later completion. Use when generating ADR documents from extracted decisions.

ADR Writing

Overview

Generate Architectural Decision Records (ADRs) following the MADR template with systematic completeness checking.

Quick Reference

Copy┌─────────────┐     ┌──────────────┐     ┌─────────────┐
│  SEQUENCE   │ ──▶ │   EXPLORE    │ ──▶ │    FILL     │
│  (get next  │     │  (context,   │     │  (template  │
│   number)   │     │   ADRs)      │     │   sections) │
└─────────────┘     └──────────────┘     └─────────────┘
       │                                        │
       │                                        ▼
       │                                 ┌─────────────┐
       │                                 │   VERIFY    │
       │                                 │  (DoD       │
       └─────────────────────────────────│   checklist)│
                                         └─────────────┘

When To Use

• Documenting architectural decisions from extracted requirements
• Converting meeting notes or discussions to formal ADRs
• Recording technical choices from PR discussions
• Creating decision records from design documents

Workflow

Step 1: Get Sequence Number

If a number was pre-assigned (e.g., when called from /beagle:write-adr with parallel writes):

• Use the pre-assigned number directly
• Do NOT call the script - this prevents duplicate numbers in parallel execution

If no number was pre-assigned (standalone use):

Copypython scripts/next_adr_number.py

This outputs the next available ADR number (e.g., 0003).

For parallel allocation (used by parent commands):

Copypython scripts/next_adr_number.py --count 3
# Outputs: 0003, 0004, 0005 (one per line)

Step 2: Explore Context

Before writing, gather additional context:

1. Related code - Find implementations affected by this decision
2. Existing ADRs - Check docs/adrs/ for related or superseded decisions
3. Discussion sources - PRs, issues, or documents referenced in decision

Step 3: Load Template

Load references/madr-template.md for the official MADR structure.

Step 4: Fill Sections

Populate each section from your decision data:

Step 5: Apply Definition of Done

Load references/definition-of-done.md and verify E.C.A.D.R. criteria:

• Explicit problem statement
• Comprehensive options analysis
• Actionable decision
• Documented consequences
• Reviewable by stakeholders

Step 6: Mark Gaps

For sections that cannot be filled from available data, insert investigation prompts:

Copy* [INVESTIGATE: Review PR #42 discussion for additional drivers]
* [INVESTIGATE: Confirm with security team on compliance requirements]
* [INVESTIGATE: Benchmark performance of Option 2 vs Option 3]

These prompts signal incomplete sections for later follow-up.

Step 7: Write File

IMPORTANT: Every ADR MUST start with YAML frontmatter.

The frontmatter block is REQUIRED and must include at minimum:

Copy---
status: draft
date: YYYY-MM-DD
---

Full frontmatter template:

Copy---
status: draft
date: 2024-01-15
decision-makers: [alice, bob]
consulted: []
informed: []
---

Validation: Before writing the file, verify the content starts with --- followed by valid YAML frontmatter. If frontmatter is missing, add it before writing.

Save to docs/adrs/NNNN-slugified-title.md:

Copydocs/adrs/0003-use-postgresql-for-user-data.md
docs/adrs/0004-adopt-event-sourcing-pattern.md
docs/adrs/0005-migrate-to-kubernetes.md

Step 8: Verify Frontmatter

After writing, confirm the file:

1. Starts with --- on the first line
2. Contains status: draft (or other valid status)
3. Contains date: YYYY-MM-DD with actual date
4. Ends frontmatter with --- before the title

File Naming Convention

Format: NNNN-slugified-title.md

Reference Files

• references/madr-template.md - Official MADR template structure
• references/definition-of-done.md - E.C.A.D.R. quality criteria

Output Example

Copy---
status: draft
date: 2024-01-15
decision-makers: [alice, bob]
---

# Use PostgreSQL for User Data Storage

## Context and Problem Statement

We need a database for user account data...

## Decision Drivers

* Data integrity requirements
* Query flexibility needs
* [INVESTIGATE: Confirm scaling projections with infrastructure team]

## Considered Options

* PostgreSQL
* MongoDB
* CockroachDB

## Decision Outcome

Chosen option: PostgreSQL, because...

## Consequences

### Good

* ACID compliance ensures data integrity

### Bad

* Requires more upfront schema design

### Neutral

* Team has moderate PostgreSQL experience