Genesis Data Agent's Toolkit
Field Mapping Tools
Create and manage field-mapping projects, configure specialized mapping agents, execute mapping tasks, and capture human input for high-quality data transformations.
Overview
Tool Name
Purpose
The field_mapping_tools enable systematic field-to-field mapping for data integration and transformation. Use them to initialize projects, create specialized mapping agents, run mapping tasks, and incorporate human review where decisions are ambiguous.Functions Available
field_mapping_delete_project: Remove a field-mapping project and its stored configuration after confirmation.field_mapping_init_project: Initialize a new field-mapping project with source and target settings, methodology, and stakeholders.field_mapping_create_bot: Create a specialized mapping agent aligned to a domain or task, with optional rules and validation criteria.field_mapping_run_todo: Execute a specific mapping todo in automated, interactive, or validation mode and return results.field_mapping_handle_user_answers: Process a user’s responses for an interactive mapping session and continue the workflow.
Key Features
Project Setup
Initialize structured mapping projects with clear scope, roles, and timelines.
Specialized Data Agents
Spin up mapping agents tailored to domains and rules for repeatable execution.
Task Execution
Run mapping todos with automated analysis or human-in-the-loop validation.
Interactive Decisions
Capture user responses at decision points to finalize mappings confidently.
Project deletion is permanent. If there is any chance you will need the configuration later, create a backup before calling the delete function.
Input Parameters for Each Function
field_mapping_delete_project
| Name | Definition | Format |
|---|---|---|
| project_id | Unique project identifier. | String (required) |
| confirmation | Safety flag to confirm deletion. | Boolean required |
| backup_config | Create a backup before deletion. | Boolean |
field_mapping_init_project
| Name | Definition | Format |
|---|---|---|
| project_name | Name for the new project. | String (required) |
| source_config | Connection and schema info for source systems. | Object required |
| target_config | Connection and schema info for target systems. | Object required |
| mapping_methodology | Approach such as rule-based or statistical. | String |
| project_description | Narrative description of scope and requirements. | String |
| stakeholders | People and roles involved. | Array |
| timeline | Milestones or delivery windows. | Object |
field_mapping_create_bot
| Name | Definition | Format |
|---|---|---|
| project_id | Target project that will own the agent. | String (required) |
| bot_name | Data Agent display name. | String (required) |
| bot_specialization | Domain or task focus, for example finance or claims. | String (required) |
| source_systems | Systems the data agents will touch. | Array |
| mapping_rules | Predefined rules and transforms. | Object |
| validation_criteria | Acceptance rules for mapped fields. | Object |
field_mapping_run_todo
| Name | Definition | Format |
|---|---|---|
| project_id | Project that contains the todo. | String (required) |
| todo_id | Identifier of the mapping task. | String (required) |
| execution_mode | How to run the task: automated, interactive, or validation. | String |
| user_context | Extra information or constraints for this run. | Object |
| validation_required | Require a user to approve results before completion. | Boolean |
field_mapping_handle_user_answers
| Name | Definition | Format |
|---|---|---|
| project_id | Project that owns the interactive session. | String (required) |
| session_id | Interactive session identifier. | String (required) |
| user_responses | Answers to questions the workflow posed. | Object required |
| continue_workflow | Continue to the next step after applying answers. | Boolean |
| save_decisions | Persist choices for future automation. | Boolean |
Use Cases
- System migration Map legacy ERP fields to a modern warehouse model with validation gates.
- ETL harmonization Normalize disparate source fields to a canonical schema with reusable rules.
- Large-scale onboarding Use specialized agents to propose mappings, then finalize via interactive reviews.
- Reusable templates Save and reapply mapping rules across similar projects to speed delivery.
- Governed transformations Enforce validation criteria and stakeholder approvals before promotion.
Workflow/How It Works
- Initialize a project with source and target configurations using
field_mapping_init_project. - Create a specialized mapping agent with domain rules via
field_mapping_create_bot. - Execute todos using
field_mapping_run_todoin the appropriate mode. - Review interactive prompts through
field_mapping_handle_user_answersand capture decisions. - Retire finished projects with
field_mapping_delete_projectwhen appropriate.
Integration Relevance
- project_manager_tools to track milestones and approvals.
- data_connector_tools to validate connectivity to source and target systems.
- make_baby_bot to create domain-specific mapping agents.
- file_manager_tools to store mapping specs, evidence, and sign-offs.
- delegate_work to orchestrate complex multi-agent mapping initiatives.
Configuration Details
- Provide accurate connection info and schema naming in source and target configs.
- Choose a mapping methodology that matches data complexity and governance needs.
- Align validation criteria with business rules to avoid rework.
- Define sensible session timeouts for interactive work to prevent stalled runs.
- Keep stakeholders and timelines current to ensure accountability.
Limitations or Notes
- Project deletion cannot be undone without a prior backup.
- Interactive sessions depend on user responsiveness and may pause indefinitely.
- Mapping quality is constrained by source data completeness and cleanliness.
- Very large datasets may require performance tuning or staged execution.
- Cross-system data type differences may require explicit conversion rules.
- Specialized agents may need additional tool permissions before execution.
Output
- Project initialization details including project id, configuration summary, and next steps.
- Data Agent creation confirmation with agent id and specialization profile.
- Todo results such as mapping suggestions, confidence scores, validation status, and logs.
- Interactive prompts and follow-up instructions when decisions are required.
- Deletion confirmation with optional backup reference.
- Error messages with actionable guidance for resolution.