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upsert_rows

Insert new rows or update existing rows in a Coda table using key columns to match records. Supports bulk operations for efficient data synchronization.

Instructions

Insert new rows or update existing rows in a table based on key columns - ideal for bulk operations

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_idYes
table_id_or_nameYes
rows_dataYes
key_columnsNo
disable_parsingNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYesAn arbitrary unique identifier for this request.
added_row_idsNoRow IDs for rows that will be added. Only applicable when keyColumns is not set or empty.
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool can insert or update rows, but it does not explain behavior when key_columns is null, what happens if values conflict, or any side effects like overwriting. The description is minimally transparent but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys the core purpose. However, it could benefit from a brief breakdown of key parameters for improved structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters, no schema descriptions, and an output schema (not shown), the description should provide more context about required fields (doc_id, table_id_or_name), the nature of RowEdit, and the role of disable_parsing. The current description is insufficient for an agent to reliably construct valid calls.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, meaning the input schema provides no descriptions for the 5 parameters. The tool description only mentions 'key columns' and 'bulk operations,' adding little meaning beyond the parameter names. It does not explain how rows_data relates to key_columns or the format of edits.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('insert new rows or update existing rows'), the resource ('table'), the mechanism ('based on key columns'), and the use case ('ideal for bulk operations'). It effectively distinguishes this from single-row tools like 'update_row' or 'delete_row'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'ideal for bulk operations' but does not provide explicit guidance on when to use this tool over siblings, nor does it state prerequisite conditions (e.g., table must exist) or when not to use it. The context is implied but not fully spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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