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Coda List Columns

coda_list_columns
Read-onlyIdempotent

List all columns in a Coda table to get schema details like names, types, and IDs before inserting or updating row data.

Instructions

List all columns in a Coda table.

Returns column metadata including name, ID, type (text, number, date, etc.), and configuration. Column IDs are internal identifiers — use column names when working with row data. This is the table schema — call this before inserting or updating rows to know the available columns and their types.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of columns to return (1-200)
cursorNoPagination cursor from a previous response
doc_idYesThe doc ID containing the table
table_id_or_nameYesTable ID or name to list columns from

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.14

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish readOnly, idempotent and openWorld, so the bar is lower, yet the description still adds real context: column IDs are internal identifiers and names should be used with row data. It omits pagination behavior despite the limit/cursor parameters, keeping it short of a 5.

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?

Four sentences, all front-loaded and purposeful, with the core action first and the workflow guidance last. The return-field enumeration slightly overlaps the output schema, but nothing is wasted.

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, rich annotations and full param coverage, the description only needs to add workflow context, which it does via the pre-write recommendation and the ID-vs-name caveat. Pagination semantics for limit/cursor are the one notable omission.

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 limit, cursor, doc_id and table_id_or_name are already documented. The description adds only the conceptual ID-vs-name distinction, which is the expected baseline when the schema does the heavy lifting.

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 ('List all columns in a Coda table') and the 'all columns' scope implicitly separates it from the singular coda_get_column sibling. An agent can tell what it returns without opening either schema.

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

Usage Guidelines4/5

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

Explicitly says to 'call this before inserting or updating rows to know the available columns and their types', which is a concrete when-to-use condition tied to coda_insert_rows/coda_update_row. It does not, however, name coda_get_column as the alternative for fetching a single column.

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