Write ADR
Generate Architecture Decision Records (ADRs) from decisions made during the current session.
Workflow Overview
- •Context - Gather repository context and existing ADRs
- •Extract - Analyze conversation for decisions using a subagent
- •Confirm - Present decisions to user for selection
- •Write - Generate ADRs in parallel using subagents
- •Report - Summarize created files and status
- •Verify - Validate generated ADRs against Definition of Done
Step 1: Gather Context
# Get current branch and recent commits git branch --show-current git log --oneline -5 # Check for existing ADRs ls docs/adrs/ 2>/dev/null || echo "No ADR directory found" # Count existing ADRs for numbering find docs/adrs -name "*.md" 2>/dev/null | wc -l
This context helps the ADR writer:
- •Reference related commits in the ADR
- •Avoid duplicate ADRs for already-documented decisions
- •Determine correct sequence numbering
Step 2: Extract Decisions
Launch a subagent to analyze the current conversation for architectural decisions:
Task(
description: "Analyze conversation and extract architectural decisions",
model: "sonnet",
prompt: |
Load the skill: Skill(skill: "beagle-analysis:adr-decision-extraction")
Analyze the conversation for decisions that warrant ADRs:
- Technology choices, architecture patterns, design trade-offs
- Rejected alternatives, significant implementation approaches
Return JSON:
{
"decisions": [
{
"id": 1,
"title": "Use PostgreSQL for primary datastore",
"context": "Brief context about why this came up",
"decision": "What was decided",
"alternatives": ["What was considered but rejected"],
"rationale": "Why this choice was made"
}
]
}
)
If the subagent returns an empty decisions array, skip to Step 5 with message: "No architectural decisions detected in this session."
Step 3: Confirm with User
Display all extracted decisions with full details, then ask user to select:
## Detected Decisions ### 1. Use PostgreSQL for primary datastore **Confidence:** high **Problem:** Need ACID transactions for financial records **Decision:** PostgreSQL for user data storage **Alternatives discussed:** - MongoDB - SQLite **Rationale:** ACID compliance, team familiarity, mature ecosystem **Source:** Discussion about database selection in planning phase --- ### 2. Implement event sourcing for audit trail **Confidence:** medium **Problem:** Compliance requires complete audit history **Decision:** Event sourcing pattern for state changes **Alternatives discussed:** - Database triggers - Application-level logging **Rationale:** Immutable audit trail, temporal queries, debugging capability **Source:** Compliance requirements discussion --- ## Selection Which decisions should I write ADRs for? - Enter numbers (e.g., "1,2" or "1-2"), "all", or "none" to skip
Important: Always display the full decision details (problem, decision, alternatives, rationale) from the extraction output BEFORE asking for selection. Do not truncate to just title and context.
Parse user response:
- •
"all"- Process all decisions - •
"none"or empty - Skip with message "No ADRs will be created." - •
"1,2"or"1-2"- Process specified decisions
Step 4: Write ADRs (Parallel)
Pre-allocate ADR numbers before launching subagents to prevent numbering conflicts:
# Pre-allocate numbers for all confirmed decisions # Example: If user selected 3 decisions python skills/adr-writing/scripts/next_adr_number.py --count 3 # Output: # 0003 # 0004 # 0005
Assign each pre-allocated number to its corresponding decision before launching subagents.
For each confirmed decision, launch an ADR Writer subagent in background with its pre-assigned number:
Task(
description: "Write ADR for: {decision.title}",
model: "sonnet",
run_in_background: true,
prompt: |
Load the skill: Skill(skill: "beagle-analysis:adr-writing")
Write an ADR for this decision:
```json
{decision JSON}
```
**IMPORTANT: Use this pre-assigned ADR number: {assigned_number}**
Instructions:
1. Explore codebase for additional context
2. Write MADR-formatted ADR to docs/adr/
3. Use the pre-assigned number {assigned_number} - DO NOT call next_adr_number.py
4. Filename format: {assigned_number}-slugified-title.md
5. Return created file path
)
Critical: Pass the pre-allocated number to each subagent. Subagents must NOT call next_adr_number.py themselves - this causes duplicate numbers when running in parallel.
All subagents run in parallel. Wait for all to complete before proceeding.
Step 5: Report Results
Collect outputs from all subagents and present summary:
## ADR Generation Complete | File | Decision | Status | |------|----------|--------| | docs/adr/0003-use-postgresql.md | Use PostgreSQL for primary datastore | Draft | ### Next Steps - Review generated ADRs for accuracy - Update status from "proposed" to "accepted" when finalized ### Gaps Requiring Investigation - [List any decisions where subagent noted missing context]
If no decisions were processed:
No ADRs were created. Run this command again after making architectural decisions.
Step 6: Verify Generated ADRs
For each created ADR, validate against Definition of Done:
## Verification Checklist | ADR | E | C | A | D | R | Status | |-----|---|---|---|---|---|--------| | 0003-use-postgresql.md | ✓ | ✓ | ✓ | ⚠ | ✗ | Incomplete | Legend: E=Evidence, C=Criteria, A=Agreement, D=Documentation, R=Realization
Verification steps:
- •Open each generated ADR file
- •Confirm filename follows
NNNN-slugified-title.mdpattern - •Verify YAML frontmatter exists at file start:
- •File MUST begin with
--- - •Contains
status: draft(or valid status) - •Contains
date: YYYY-MM-DD(actual date) - •Ends with
---before title - •If frontmatter is missing, add it immediately
- •File MUST begin with
- •Review for
[INVESTIGATE]prompts - these need follow-up - •Verify at least 2 alternatives are documented
- •Confirm consequences section has both Good and Bad items
If gaps exist:
- •Keep status as
draftuntil gaps are resolved - •Use
[INVESTIGATE]prompts to guide follow-up session - •Schedule review with stakeholders before changing to
accepted
Output Location
ADRs are written to docs/adr/. If no ADR directory exists, create it with an initial 0000-use-madr.md template record.
MADR Format Reference
---
status: draft
date: YYYY-MM-DD
---
# {TITLE}
## Context and Problem Statement
{What is the issue motivating this decision?}
## Decision Drivers
* {driver 1}
* {driver 2}
## Decision Outcome
Chosen option: "{option}", because {reason}.
### Consequences
* Good, because {positive}
* Bad, because {negative}