Skip to main content
Glama

Coda Push Button

coda_push_button

Trigger a button in a Coda table row to run its configured action, such as an automation or row update, and return a request ID for async tracking.

Instructions

Push a button in a Coda table row.

Triggers the button's configured action (e.g. run automation, modify row). The button must be in a Button-type column. The effect depends on the button's configuration in the Coda doc. Returns a requestId for async mutation tracking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doc_idYesThe doc ID containing the table
row_id_or_nameYesRow ID or name containing the button
table_id_or_nameYesTable ID or name
column_id_or_nameYesColumn ID or name of the button column

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.14

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare this is a non-read-only, open-world mutation, but the description adds meaningful context beyond them: the effect is config-dependent and unknowable ahead of time, and the call returns a requestId for async mutation tracking. That async/idempotency-relevant detail is genuinely useful for a mutating tool.

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 core action is front-loaded in the first sentence, and each subsequent sentence adds a distinct fact (trigger semantics, precondition, return value) with no redundancy. It is appropriately sized for a four-parameter mutation tool.

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 and annotations covering the safety profile, the description supplies the necessary extras: the precondition, the config-dependent effect, and the async-tracking requestId. The main remaining gap is routing guidance against coda_trigger_automation, but the operational picture is complete.

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 (doc_id, table_id_or_name, row_id_or_name, column_id_or_name). The description adds the constraint that column_id_or_name must point to a Button-type column, but this is already stated elsewhere in the prose, so it stays at the baseline 3.

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

Purpose4/5

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

The description states a specific verb (push) and resource (a button in a Coda table row) and explains the resulting action (runs the button's configured automation or modifies the row). It is clear what the tool does, though it does not explicitly distinguish itself from the sibling coda_trigger_automation, which an agent might confuse it with.

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?

It provides a precondition (the target must be a Button-type column) that implies when the tool is applicable, but it never states when to prefer this over the closely related coda_trigger_automation or other mutation tools. Usage is implied rather than explicitly guided.

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