vector-assist-modify-spec

The “vector-assist-modify-spec” tool modifies an existing vector specification with new parameters or overrides, recalculating the generated SQL recommendations to match the updated requirements.

3 minute read

About

The vector-assist-modify-spec tool modifies an existing vector specification (identified by a required spec_id) with new parameters or overrides. Upon modification, it automatically recalculates and refreshes the list of generated recommendations by vector_assist.define-spec to match the updated spec requirements.

Use this tool when a user or agent wants to adjust or fine-tune the configuration of an already defined vector spec (such as changing the target recall, embedding model, or quantization) before actually executing the setup commands. Under the hood, this tool connects to the target database and executes the vector_assist.modify_spec function to generate the updated specifications.

Compatible Sources

This tool can be used with the following database sources:

Source Name
Cloud SQL for PostgreSQL Source

Requirements

Tip

Ensure that your target PostgreSQL database has the required vector_assist extension installed, and that the vector_assist.modify_spec function is available in order for this tool to execute successfully.

Parameters

The tool takes the following input parameters:

Parameter	Type	Description	Required
`spec_id`	string	Unique ID of the vector specification to modify.	Yes
`table_name`	string	New table name for the vector workload setup.	No
`schema_name`	string	New schema name containing the target table.	No
`vector_column_name`	string	New name for the column containing vector embeddings.	No
`text_column_name`	string	New name for the text column for vector search.	No
`vector_index_type`	string	New vector index type (‘hnsw’, ‘ivfflat’, or ‘scann’).	No
`embeddings_available`	boolean	Update if vector embeddings already exist in the table.	No
`num_vectors`	integer	Update the expected total number of vectors.	No
`dimensionality`	integer	Update the dimension of vectors or the embedding model.	No
`embedding_model`	string	Update the model used for generating vector embeddings.	No
`prefilter_column_names`	array	Update the columns used for prefiltering vector queries.	No
`distance_func`	string	Update the distance function (‘cosine’, ‘ip’, ’l2’, ’l1’).	No
`quantization`	string	Update the quantization method (’none’, ‘halfvec’, ‘bit’).	No
`memory_budget_kb`	integer	Update maximum memory (in KB) for index building.	No
`target_recall`	float	Update the target recall rate for the index.	No
`target_top_k`	integer	Update the number of top results (top-K) to retrieve.	No
`tune_vector_index`	boolean	Update whether automatic tuning is required for the index.	No

Note Parameters are marked as required or optional based on the vector assist function definitions. The function may perform further validation on optional parameters to ensure all necessary data is available before returning a response.

Example

kind: tool
name: modify_spec
type: vector-assist-modify-spec
source: my-database-source
description: "This tool modifies an existing vector specification (identified by a required spec_id) with new parameters or overrides. Upon modification, it automatically recalculates and refreshes the list of generated SQL recommendations to match the updated requirements. Use this tool when a user wants to adjust or fine-tune the configuration of an already defined vector spec (such as changing the target recall, embedding model, or quantization) before actually executing the setup commands."

Reference

field	type	required	description
type	string	true	Must be “vector-assist-modify-spec”.
source	string	true	Name of the source the SQL should execute on.
description	string	false	Description of the tool that is passed to the agent.

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Last modified April 13, 2026: chore(main): release 1.1.0 (#3024) (da6f5f8)