Airtable Master

This is NOT a user-facing skill. It's a shared resource library.

Purpose

Provides shared resources to eliminate duplication across:

• airtable-connect

• Connect to bases, discover schema

• airtable-query

• Query records with filters

• airtable-sync

• Import/export records

Instead of loading this skill, users invoke the specific skill above.

Architecture: DRY Principle

Problem solved: Multiple Airtable skills would have duplicated content (setup instructions, API docs, error handling).

Solution: Extract shared content into references/ and scripts/ .

Result: Single source of truth, reduced context per skill.

Shared Resources

references/

setup-guide.md - Complete setup wizard

• Creating Personal Access Token (PAT)

• Configuring .env file

• Selecting scopes

• Validation steps

api-reference.md - API patterns

• Base URL and headers

• Key endpoints (bases, tables, records)

• Pagination

• Batch operations

• Rate limits

error-handling.md - Troubleshooting

• HTTP error codes (401, 403, 404, 422, 429)

• Recovery patterns

• Debugging tips

field-types.md - Field type reference

• All 20+ Airtable field types

• Read and write formats

• Type-specific validation

scripts/

Configuration & Setup

check_airtable_config.py - Pre-flight validation

python check_airtable_config.py [--verbose] [--json]

Argument Required Default Description

--verbose / -v

No False Show detailed output

--json

No False Output structured JSON for AI consumption

Exit codes: 0=configured, 1=partial (no bases), 2=not configured

When to Use: Run this FIRST before any Airtable operation. Use to validate PAT is configured, test API connection, check base access, or diagnose authentication issues.

setup_airtable.py - Interactive setup wizard

python setup_airtable.py [--non-interactive] [--api-key KEY]

Argument Required Default Description

--non-interactive

No False Skip prompts (requires API key)

--api-key

No

API key for non-interactive mode

Default: Runs interactively. Guides through PAT creation, tests connection, saves to .env , auto-runs base discovery.

When to Use: Use when Airtable integration needs initial setup, when check_airtable_config.py returns exit code 2, or when user needs to reconfigure credentials or switch workspaces.

discover_bases.py - Base discovery (GET /meta/bases)

python discover_bases.py [--refresh] [--json] [--with-schema]

Argument Required Default Description

--refresh

No False Force re-discovery even if cache exists

--json

No False Output as JSON only (no progress messages)

--with-schema

No False Also fetch table schemas (slower)

Saves to: 01-memory/integrations/airtable-bases.yaml

When to Use: Use when user asks "what bases do I have", "list my airtable bases", "show tables", after adding new bases, or when base/table name resolution fails (--refresh to update cache).

Record Operations

query_records.py - Query records from table (GET /{baseId}/{tableIdOrName})

python query_records.py --base BASE --table TABLE [--filter FORMULA] [--fields FIELDS] [--view VIEW] [--sort FIELD] [--limit N] [--json] [--verbose]

Argument Required Default Description

--base

Yes

Base ID (appXXX) or name

--table

Yes

Table ID (tblXXX) or name

--filter

No

Airtable formula filter

--fields

No

Comma-separated field names to retrieve

--view

No

View ID or name

--sort

No

Sort field (prefix with - for descending)

--limit

No

Max records to return

--json

No False Output as JSON

--verbose / -v

No False Show debug info

Filter Formula Examples:

--filter "{Status}='Active'" --filter "AND({Status}='Active', {Priority}='High')" --filter "SEARCH('john', LOWER({Name}))" --filter "{Due Date} < TODAY()"

When to Use: Use when user wants to read records from a table, search with filters, list data from Airtable, or retrieve specific records. Supports Airtable formula syntax for complex filters.

manage_records.py - CRUD operations (POST/PATCH/PUT/DELETE /{baseId}/{tableIdOrName})

Create record(s)

python manage_records.py create --base BASE --table TABLE --data JSON [--file FILE] [--typecast] [--json] [--verbose]

Update record(s)

python manage_records.py update --base BASE --table TABLE --record RECID --data JSON [--file FILE] [--typecast] [--replace] [--json] [--verbose]

Delete record(s)

python manage_records.py delete --base BASE --table TABLE --record RECID [--file FILE] [--json] [--verbose]

Argument Required Default Description

action

Yes

Action: create , update , delete (positional)

--base

Yes

Base ID (appXXX) or name

--table

Yes

Table ID (tblXXX) or name

--record

No*

Record ID (for update/delete single record)

--data

No*

JSON data for fields

--file

No*

JSON file with record(s) data

--typecast

No False Enable automatic type conversion

--replace

No False Replace mode for update (PUT vs PATCH)

--json

No False Output as JSON

--verbose / -v

No False Show debug info

*For create: --data or --file required *For update: --record

• --data or --file required *For delete: --record or --file required

Usage Examples:

Create a single record

python manage_records.py create --base "My CRM" --table "Contacts"
--data '{"Name": "John Doe", "Email": "john@example.com"}'

Create multiple records from file

python manage_records.py create --base appXXX --table tblYYY --file records.json

Update a record

python manage_records.py update --base "Tasks" --table "Tasks"
--record recXXX --data '{"Status": "Done"}'

Delete a record

python manage_records.py delete --base "Tasks" --table "Tasks" --record recXXX

Batch operations with typecast

python manage_records.py create --base "CRM" --table "Leads"
--file leads.json --typecast

Batch Limits: Max 10 records per API call (script handles batching automatically)

When to Use: Use create when user wants to add new records, update to modify existing records (PATCH=partial, PUT=replace), delete to remove records. Supports batch operations from JSON files.

Intelligent Error Detection Flow

When an Airtable skill fails due to missing configuration, the AI should:

Step 1: Run Config Check with JSON Output

python 00-system/skills/airtable/airtable-master/scripts/check_airtable_config.py --json

Step 2: Parse the ai_action Field

The JSON output includes an ai_action field that tells the AI what to do:

ai_action What to Do

proceed_with_operation

Config OK, continue with the original operation

proceed_with_warning

Partial config (API works but no bases accessible)

prompt_for_api_key

Ask user: "I need your Airtable API key. Get one at https://airtable.com/create/tokens"

run_setup_wizard

Run: python 00-system/skills/airtable/airtable-master/scripts/setup_airtable.py

Step 3: Help User Fix Issues

If ai_action is prompt_for_api_key :

• Tell user: "Airtable integration needs setup. I need your Personal Access Token (PAT)."

• Show them: "Get one at: https://airtable.com/create/tokens"

• Guide them through scopes: "Add scopes: data.records:read, data.records:write, schema.bases:read"

• Ask: "Paste your Airtable PAT here (starts with 'pat.'):"

• Once they provide it, write directly to .env :

Edit .env file to add:

AIRTABLE_API_KEY=pat.their_token_here

• Re-run config check to verify

JSON Output Structure

{ "status": "not_configured", "exit_code": 2, "ai_action": "prompt_for_api_key", "missing": [ {"item": "AIRTABLE_API_KEY", "required": true, "location": ".env"} ], "fix_instructions": [...], "env_template": "AIRTABLE_API_KEY=pat.YOUR_TOKEN_HERE", "setup_wizard": "python 00-system/skills/airtable/airtable-master/scripts/setup_airtable.py" }

How Skills Reference This

Each skill loads shared resources only when needed (progressive disclosure):

airtable-connect uses:

• check_airtable_config.py (validate before connection)

• discover_bases.py (find and cache bases)

• api-reference.md (schema endpoints)

• error-handling.md (troubleshooting)

airtable-query uses:

• check_airtable_config.py (validate before query)

• query_records.py (list/filter records)

• api-reference.md (query patterns)

• field-types.md (interpret results)

airtable-sync uses:

• check_airtable_config.py (validate before sync)

• manage_records.py (CRUD operations)

• api-reference.md (batch patterns)

• error-handling.md (recovery)

Usage Example

User says: "query my Projects base in Airtable"

What happens:

• AI loads airtable-connect (NOT airtable-master)

• airtable-connect SKILL.md says: "Run check_airtable_config.py first"

• AI executes: python 00-system/skills/airtable/airtable-master/scripts/check_airtable_config.py --json

• If exit code 2, AI prompts user for API key and helps them set up

• If exit code 0, AI executes: python 00-system/skills/airtable/airtable-master/scripts/query_records.py --base "Projects"

• If errors occur, AI loads: airtable-master/references/error-handling.md

airtable-master is NEVER loaded directly - it's just a resource library.

Key Differences from Notion

Aspect Airtable Notion

Auth Personal Access Token (PAT) Integration Token

Rate Limit 5 req/s per base 3 req/s

Batch Size 10 records Variable

Pagination Offset-based Cursor-based

Field Types 20+ types 20+ property types

Version: 1.3 Created: 2025-12-11 Updated: 2025-12-11 Status: Production Ready

Changelog:

• v1.3: Added "When to Use" sections to all 5 scripts for AI routing guidance

• v1.2: Added comprehensive script argument documentation with usage examples and argument tables

• v1.1: Added Intelligent Error Detection Flow with --json support, added setup_airtable.py

• v1.0: Initial release