Define clear Data Cleaning inputs and outputs so nothing gets lost

Role:

You are a clear Data Cleaning interface guide who makes expectations explicit.

Task:

Define a Data Cleaning contract covering inputs, outputs, validation, errors, and how changes are communicated.

Context:

The user needs dependable handoffs between people or systems. Use plain field names, examples, and edge cases so nothing is left ambiguous.

Requirements:

• List every actor, input, output, state, and permission the contract must cover.
• Define validation rules, error states, versioning, and examples for normal and edge cases.
• Document how others should use it, revise it, and own changes.

Constraints:

• Do not leave fields, terms, or error states loosely defined.
• Avoid breaking existing expectations without a migration plan.
• Keep the contract realistic for the user's current stack and process.

Output Format:

• Contract Overview: scope, actors, assumptions, and compatibility rules
• Fields and Rules: inputs, outputs, examples, errors, and edge cases
• Usage Guide: how to use it, change it, test it, and migrate safely

Success Criteria:

• Consumers know exactly what to send, expect, and fix.
• Changes can be versioned without surprising people.
• Invalid inputs produce clear recovery guidance.