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Get Coda Column

coda_get_column
Read-onlyIdempotent

Retrieve detailed information about a specific column in a Coda table, including its formula, type, and currency or number format settings.

Instructions

Get detailed information about a specific column, including its formula and format.

Especially useful to inspect calculated column formulas and currency/number format settings.

Args:

  • doc_id (string): The document ID

  • table_id (string): The table ID or name

  • column_id (string): The column ID (e.g. "c-ABC123") or name

  • response_format: 'markdown' or 'json'

Returns: Column details including id, name, type, format (currency code, precision), formula if calculated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_idYesCoda document ID
table_idYesTable ID or name
column_idYesColumn ID (e.g. 'c-ABC123') or name
response_formatNoOutput format: 'markdown' for human-readable, 'json' for machine-readablemarkdown
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description adds value by detailing the return contents (id, name, type, format, formula). No contradictions exist.

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?

The description is concise with three sentences, front-loads the purpose, and includes a clear parameter list and return description. No unnecessary words.

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?

Given the annotations cover safety and the schema covers parameters, the description adequately explains the return value. It is complete for a simple read operation, though could mention error cases like column not found, but that is not essential for tool selection.

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?

The input schema already provides descriptions for all 4 parameters (100% coverage). The description repeats the parameter list and adds a brief return summary, but does not add significant new meaning beyond the schema.

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 'Get detailed information about a specific column', with a specific verb and resource. It also mentions including formula and format, and is distinct from siblings like coda_list_columns (which lists columns) and coda_get_table.

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?

The description notes it is 'especially useful to inspect calculated column formulas and currency/number format settings', providing clear context for when to use it. However, it does not explicitly exclude alternatives or mention when not to use it.

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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