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vish288

mcp-coda

by vish288
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Coda List Columns

coda_list_columns
Read-onlyIdempotent

List all columns in a Coda table and return their names, IDs, types, and configuration so you can verify the schema before inserting or updating rows.

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

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.1
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "type": "string"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "type": "object",
-  "x-fastmcp-wrap-result": true
-}New value: +null
  2. 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 cover the safety profile (readOnlyHint, idempotentHint, openWorldHint), so the bar is lower, and the description still adds real context: the shape of the returned metadata and the caveat that column IDs are internal identifiers that should not be used with row data. It stops short of disclosing pagination behavior, which matters because limit/cursor exist.

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?

Front-loaded with the core action, then layers return shape and the ID-vs-name caveat in three short sentences. Every sentence carries information, though the parenthetical type list ('text, number, date, etc.') is slightly loose padding.

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 no output schema, the description does the work of describing the return payload (name, ID, type, configuration) and its purpose as a schema pre-check, which is the key thing an agent needs. The notable omission is any mention of pagination despite the cursor/limit parameters and a default limit of 100.

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% and all four parameters (doc_id, table_id_or_name, limit, cursor) are documented in the schema itself. The description adds no format, naming, or scoping detail about the parameters, so it does not go beyond the structured data.

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 immediately characterizes the result as the table schema, which separates it from row-level siblings like coda_list_rows or coda_insert_rows. It also implicitly contrasts with coda_get_column (single column) by scoping to 'all columns'.

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?

Gives an explicit workflow trigger: 'call this before inserting or updating rows to know the available columns and their types.' It also advises using column names rather than IDs when working with row data. It does not, however, say when to prefer coda_get_column or coda_list_tables over this tool, so no true alternatives/exclusions are stated.

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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