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Coda Get Row

coda_get_row
Read-onlyIdempotent

Fetch a single row from a Coda table by row ID or display column value, returning all its column values. Use when you need one specific row's data.

Instructions

Get a single row from a Coda table by ID or display column value.

Returns all column values for the specified row. Use this when you have a specific row ID or know the display column value. For querying multiple rows with filters, use coda_list_rows instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_idYesThe doc ID containing the table
row_id_or_nameYesRow ID or name (display column value)
table_id_or_nameYesTable ID or name
use_column_namesNoUse column names (True) or IDs (False) in row values

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.14

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description adds that all column values are returned and that the display column value can serve as a key, but says nothing about pagination, rate limits, or behavior for missing rows. That is reasonable added context but not rich behavioral disclosure.

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

Conciseness5/5

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

Three tight sentences: purpose first, return value second, disambiguation last. No filler, no repetition of the title, and the routing guidance is placed where an agent will read it before committing to the call.

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

Completeness4/5

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

With an output schema present, the description need not explain return shape, and annotations carry the safety profile; the description covers purpose, keys, and the closest alternative. Slightly short of 5 only because it does not address what happens when a row is not found or how display-column matching behaves on ambiguity.

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

Parameters3/5

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

Schema description coverage is 100%, so all four parameters are already documented in the schema. The description reinforces the ID-or-display-column-value semantics of row_id_or_name and the column-name/ID distinction indirectly, but adds no syntax, format, or defaulting detail beyond the schema. Baseline 3 applies.

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?

States a specific verb and resource ('Get a single row from a Coda table'), specifies the lookup keys (ID or display column value), and names the sibling it is distinct from (coda_list_rows). An agent can distinguish it from coda_list_rows, coda_get_table, and coda_list_columns without opening any schema.

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

Usage Guidelines5/5

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

Explicitly states when to use it ('when you have a specific row ID or know the display column value') and names the alternative with its selecting condition ('For querying multiple rows with filters, use coda_list_rows instead'). Both the positive and negative routing cases are covered.

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