Write Adr
by @anderskev
Use when you want to generate Architecture Decision Records from this session. Triggers on "write ADRs", "document our decisions", "create decision records",...
clawhub install write-adrπ About This Skill
description: "Use when you want to generate Architecture Decision Records from this session. Triggers on \"write ADRs\", \"document our decisions\", \"create decision records\", \"record the choices we made\". Also useful after design discussions where decisions were reached but not documented. Does NOT extract decisions alone (use adr-decision-extraction) or provide MADR template (use adr-writing). Orchestrates the full workflow: subagent extraction, user confirmation, parallel generation, and verification." name: write-adr disable-model-invocation: true
Write ADR
Generate Architecture Decision Records (ADRs) from decisions made during the current session.
Workflow Overview
1. Context - Gather repository context and existing ADRs 2. Extract - Analyze conversation for decisions using a subagent 3. Confirm - Present decisions to user for selection 4. Write - Generate ADRs in parallel using subagents 5. Report - Summarize created files and status 6. 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 -5Check 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:
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 Decisions1. Use PostgreSQL for primary datastore
Confidence: highProblem: 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: mediumProblem: 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 decisionsStep 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 | β | β | β | β | β | Incomplete |
Legend: E=Evidence, C=Criteria, A=Agreement, D=Documentation, R=Realization
Verification steps:
1. Open each generated ADR file
2. Confirm filename follows NNNN-slugified-title.md pattern
3. 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
4. Review for [INVESTIGATE] prompts - these need follow-up
5. Verify at least 2 alternatives are documented
6. Confirm consequences section has both Good and Bad items
If gaps exist:
draft until gaps are resolved[INVESTIGATE] prompts to guide follow-up sessionacceptedOutput 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}