Schema-Triggered Patch

Schema-Triggered Patch automatically patches existing data when the MCP/schema is updated — reconciling records to align with the new schema without a full regeneration. When function implementations or names have changed, instead of regenerating an entire dataset from scratch, you provide a function mapping that specifies which functions have changed, and the system regenerates only the affected dialogue segments.

When to Use

Function names have been renamed (e.g., getUser to fetchUser)
Function implementations have changed and existing conversations need to reflect the new behavior
You want to update a subset of conversations without losing the overall dataset structure

Parameters

Parameter	Required	Description
`input`	Yes	Path to existing data file or directory
`function_mapping`	Yes	JSONL file mapping previous function names to new function names
`request`	Yes	Description of regeneration instructions
`mcp_server_url`	Yes	URL of the MCP server providing the updated schema
`domain`	No	Domain context for regeneration
`reference_doc`	No	Path to reference documentation

Function Mapping File

The function mapping is a JSONL file where each line maps a previous function name to its new name. This tells the system which conversation segments need regeneration.

{"previous": "getUser", "new": "fetchUser"}
{"previous": "createOrder", "new": "submitOrder"}

This feature uses the standard chatbot interaction flow. Describe what you need in natural language, and the CLI guides you through parameter collection and confirmation.

Using /execute

You can also run schema-triggered-patch non-interactively via /execute with a YAML config:

task: schema-triggered-patch
input: ./data/conversations.jsonl
function_mapping: ./mappings/function_changes.jsonl
request: Regenerate only the affected dialogue segments based on the function mapping.
domain: airline customer service
mcp_server_url: http://127.0.0.1:8009

Output

After a run completes, results are saved under outputs/ as a new run directory, for example:

outputs/schema-triggered-patch_output_<run_id>/

Inside the run directory:

generated_data.jsonl - The regenerated dataset in JSONL format
datapoints/ - One JSON file per sample (expanded view of generated_data.jsonl)
metadata.json - Run metadata (task type, parameters, primary files, timestamps)

The viewer provides a split view that shows regenerated segments alongside the original data for easy comparison.

Eigen AI

API Reference

Platform

Products

When to Use

Parameters

Function Mapping File

Using /execute

Output

​When to Use

​Parameters

​Function Mapping File

​Using /execute

​Output

When to Use

Parameters

Function Mapping File

Using /execute

Output