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.
Generates Architectural Decision Records using the MADR template with systematic completeness checking. Automatically assigns sequence numbers and applies Definition of Done criteria, marking incomplete sections with investigation prompts for later follow-up.
/plugin marketplace add existential-birds/beagle/plugin install beagle@existential-birdsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
references/definition-of-done.mdreferences/madr-template.mdscripts/next_adr_number.pyGenerate Architectural Decision Records (ADRs) following the MADR template with systematic completeness checking.
┌─────────────┐ ┌──────────────┐ ┌─────────────┐
│ SEQUENCE │ ──▶ │ EXPLORE │ ──▶ │ FILL │
│ (get next │ │ (context, │ │ (template │
│ number) │ │ ADRs) │ │ sections) │
└─────────────┘ └──────────────┘ └─────────────┘
│ │
│ ▼
│ ┌─────────────┐
│ │ VERIFY │
│ │ (DoD │
└─────────────────────────────────│ checklist)│
└─────────────┘
If a number was pre-assigned (e.g., when called from /beagle:write-adr with parallel writes):
If no number was pre-assigned (standalone use):
python scripts/next_adr_number.py
This outputs the next available ADR number (e.g., 0003).
For parallel allocation (used by parent commands):
python scripts/next_adr_number.py --count 3
# Outputs: 0003, 0004, 0005 (one per line)
Before writing, gather additional context:
docs/adrs/ for related or superseded decisionsLoad references/madr-template.md for the official MADR structure.
Populate each section from your decision data:
| Section | Source |
|---|---|
| Title | Decision summary (imperative mood) |
| Status | Always draft initially |
| Context | Problem statement, constraints |
| Decision Drivers | Prioritized requirements |
| Considered Options | All viable alternatives |
| Decision Outcome | Chosen option with rationale |
| Consequences | Good, bad, neutral impacts |
Load references/definition-of-done.md and verify E.C.A.D.R. criteria:
For sections that cannot be filled from available data, insert investigation prompts:
* [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.
IMPORTANT: Every ADR MUST start with YAML frontmatter.
The frontmatter block is REQUIRED and must include at minimum:
---
status: draft
date: YYYY-MM-DD
---
Full frontmatter template:
---
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:
docs/adrs/0003-use-postgresql-for-user-data.md
docs/adrs/0004-adopt-event-sourcing-pattern.md
docs/adrs/0005-migrate-to-kubernetes.md
After writing, confirm the file:
--- on the first linestatus: draft (or other valid status)date: YYYY-MM-DD with actual date--- before the titleFormat: NNNN-slugified-title.md
| Component | Rule |
|---|---|
NNNN | Zero-padded sequence number from script |
- | Separator |
slugified-title | Lowercase, hyphens, no special characters |
.md | Markdown extension |
references/madr-template.md - Official MADR template structurereferences/definition-of-done.md - E.C.A.D.R. quality criteria---
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
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