airtable-master_skill

Overview

This skill is a shared resource library for Airtable integration skills that centralizes setup guides, API patterns, error handling, field-type references, and reusable scripts. It is not intended to be loaded directly; instead, specific Airtable skills (connect, query, sync) reference these resources to avoid duplication and keep each skill focused. The library enforces the DRY principle and provides a single source of truth for Airtable operations and recovery flows.

How this skill works

The skill groups content into references (setup guide, API reference, error handling, field types) and executable scripts (config checks, setup wizard, base discovery, query, and record management). Scripts provide command-line interfaces with consistent arguments and JSON output options for AI-driven orchestration. Intelligent error detection uses a config-check script that emits an ai_action field guiding the next step (proceed, prompt for API key, or run setup).

When to use it

• When other Airtable skills need shared documentation or tooling (connect, query, sync).
• Before any Airtable operation: run the pre-flight config check to validate PAT and base access.
• When initial setup or reconfiguration of Airtable credentials is required.
• When discovering bases and table schemas or refreshing cached metadata.
• When performing queries or CRUD operations with consistent batching, pagination, and rate-limit handling.

Best practices

• Always run the config check script with --json first and follow the ai_action instructions.
• Use the interactive setup wizard for initial configuration; use non-interactive mode only for automation with secure key injection.
• Cache discovered bases but use --refresh when you add new bases or change access.
• Respect batch limits (10 records per API call) and rely on the scripts to handle batching automatically.
• Typecast only when necessary and validate field types against the field-types reference before writing data.

Example use cases

• Validate integration before running a sync: python check_airtable_config.py --json and follow ai_action.
• Discover all bases and optionally fetch schemas: python discover_bases.py --with-schema --json.
• Query a table with formula filters: python query_records.py --base "Projects" --table "Tasks" --filter "{Status}='Active'" --limit 100 --json.
• Create or update records in batches from a JSON file with typecast: python manage_records.py create --base CRM --table Leads --file leads.json --typecast.
• Automate first-time setup in CI by running setup_airtable.py --non-interactive --api-key $AIRTABLE_API_KEY.