eddytor-zero-to-table

name	eddytor-zero-to-table
description	End-to-end guided path from an empty Eddytor instance to a constrained, populated, validated table. Activates for "set up from scratch", first table, onboarding a new dataset, "I have a CSV and nothing else", or "get me started" — even without naming a specific tool.
license	CC-BY-NC-4.0
metadata	{"author":"eddytor","version":"1.0"}

Zero to Table

The full sequence for standing up master data from nothing: connect storage, land the data, constrain it, validate it. Each step links to the deep-dive skill.

Default procedure

1. Connect a storage configuration (eddytor-storage-registration)

register_s3_storage(bucket_name="mdm-prod", region="eu-west-1",
  access_key_id="...", secret_key="...")
list_storage_configs()              # capture the config_id

Nothing can be created until a storage config exists.

2. Land the data — pick one:

• Have a CSV? Infer then import (eddytor-data-import):

  infer_schema(csv_content="id,name,category\n...")   # review types + domain candidates
  import_csv(table_name="products",
    location="abfss://[e-mail]/master-data",
    primary_key_column="product_id",
    csv_content="...", non_nullable_columns=["product_id","name"])
  

• Designing from scratch? Create the table (eddytor-table-management):

  create_table(table_name="products", location="...",
    columns=[{ name:"product_id", data_type:"Utf8", nullable:false, is_primary_key:true }, ...],
    constraints=[{ name:"price_positive", expr:"price > 0" }])
  

table_name is bare (products); location is a full storage URL.

3. Constrain it (eddytor-data-quality, eddytor-domain-hierarchies)

set_column_domain(table, "status", "fixed", values=["active","discontinued","draft"])
# hierarchical domains are keyed by the parent value's UUID — read it first:
get_allowed_values(table, "category")
set_column_domain(table, "subcategory", "hierarchical",
  parent_column="category", hierarchy={ "<parent-uuid>": ["Phones","Laptops"] })

4. Validate (eddytor-data-quality)

validate_constraints(table)       # PK, NOT NULL, check expressions
validate_domain_values(table)     # domain mismatches + typo suggestions
profile_table(table)              # row count, null distribution, ranges

Fix any violations with merge_rows, then re-validate.

Gotchas

• Set domains before loading data when you can — write-time rejection beats cleanup.
• If import_csv fails (type conflict, duplicate PKs), the table is not created — fix the data and retry.
• Hierarchical hierarchy maps use parent-value UUIDs, not strings (step 3).
• Get the fully-qualified table name from list_tables for every step after creation.

Guidelines

• This skill is the map; defer to the linked skill for each step's full options.
• Confirm each step before the next: get_table_schema after create/import, get_allowed_values after setting a domain, validation before declaring done.