From atum-nocode
Design, audit, and optimize Airtable base schemas. Creates relational data models, identifies schema anti-patterns, generates migration plans, and documents table structures. Use when asked to design an Airtable schema, audit a base, optimize fields, fix relations, or document an Airtable structure.
npx claudepluginhub arnwaldn/atum-plugins-collection --plugin atum-nocodeThis skill uses the workspace's default tool permissions.
Expert en modélisation, audit et optimisation de bases Airtable.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Executes pre-written implementation plans: critically reviews, follows bite-sized steps exactly, runs verifications, tracks progress with checkpoints, uses git worktrees, stops on blockers.
Guides idea refinement into designs: explores context, asks questions one-by-one, proposes approaches, presents sections for approval, writes/review specs before coding.
Expert en modélisation, audit et optimisation de bases Airtable.
Convert business requirements into a normalized Airtable schema.
Process:
Field Type Selection Guide:
| Data Pattern | Best Field Type | Avoid |
|---|---|---|
| Fixed list of options | Single/Multiple Select | Long Text |
| Yes/No | Checkbox | Single Select with 2 options |
| Reference to another table | Linked Record | Long Text with copy-paste |
| Computed from linked records | Rollup | Formula duplicating data |
| Display from linked record | Lookup | Manual copy |
| Date with time | Date+Time field | Text field |
| Money amounts | Currency field | Number field |
| Sequential counter | Auto Number | Manual number |
| Calculated from same row | Formula | Manual entry |
| File/image | Attachment | URL field |
| User assignment | Collaborator | Single Line Text |
Analyze an existing base for anti-patterns:
Anti-Patterns Detected:
Audit via MCP Tools:
1. mcp__claude_ai_Airtable__list_bases → find target base
2. mcp__claude_ai_Airtable__list_tables_for_base → get all tables
3. mcp__claude_ai_Airtable__get_table_schema → detailed field analysis
4. mcp__claude_ai_Airtable__list_records_for_table → sample data for fill rate
Generate a complete schema doc:
# Base: [Name]
## Tables
### [Table Name] (N records)
| Field | Type | Description | Required |
|-------|------|-------------|----------|
| Name | Single Line | Primary identifier | Yes |
| Status | Single Select | Workflow state (New/Active/Done) | Yes |
| Owner | Linked Record → Users | Assigned person | No |
| Created | Created Time | Auto-generated | Auto |
### Relations
- Users 1→N Projects (via Owner field)
- Projects 1→N Tasks (via Project field)
### Views
- All Projects (Grid, default)
- Active Projects (Grid, filtered: Status = Active)
- By Owner (Kanban, grouped by Owner)
- Timeline (Timeline, by Start/End Date)
When restructuring a base:
Contacts ← Companies (N:1)
Contacts ← Deals (1:N)
Contacts ← Activities (1:N)
Deals ← Pipeline Stages (N:1 via Select)
Projects ← Tasks (1:N)
Tasks ← Subtasks (1:N, self-referencing)
Tasks ← Time Entries (1:N)
Projects ← Milestones (1:N)
Users ← Tasks (1:N via Assignee)
Content ← Authors (N:1)
Content ← Platforms (N:N via junction)
Content ← Assets (1:N)
Campaigns ← Content (1:N)
Editorial Calendar = Content view by Publish Date
Products ← Categories (N:1)
Products ← Suppliers (N:N via junction)
Products ← Stock Movements (1:N)
Warehouses ← Stock Movements (1:N)
Current Stock = Rollup(Stock Movements, SUM(quantity))