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niyogi

chatgpt-ads-manager-mcp

by niyogi

update_ad_account_spend_limit_window

Update an ad account's spend limit window by specifying its window ID and new start/end times or spend cap. Adjust spending limits to manage campaign budgets over custom time periods.

Instructions

Edit a spend limit window (inclusive start, exclusive end). Provide window_id from get/create.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_timeNoExclusive end unix seconds.
window_idYesSpend limit window ID.
start_timeNoInclusive start unix seconds.
ad_account_idNoOptional ad account ID override.
spend_limit_microsNoSpend cap in micros.
Behavior3/5

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

With no annotations, the description carries the behavioral transparency burden. It adds useful provenance (window_id must come from get/create) and boundary semantics, but it does not disclose whether omitted optional parameters leave existing values unchanged or reset them, nor any other side effects. This is a serviceable but partial disclosure for a mutation tool.

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 two brief sentences with no filler. The core action and semantic detail are front-loaded, and the second sentence supplies the one essential usage clue needed to call the tool correctly.

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

Completeness3/5

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

Together with the fully described schema, the definition is usable: it names the operation, the required ID source, and the time-window boundaries. However, for an update tool with no annotations and no output schema, it does not state partial-update behavior or what the caller should expect in return, leaving moderate contextual gaps.

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 the schema fully documents each parameter's meaning, types, an constraints. The description itself only reinforces the inclusive/exclusive start/end semantics and points to window_id provenance, adding no significant 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 states a specific verb ('Edit') and resource ('spend limit window') and clarifies the critical boundary semantics (inclusive start, exclusive end). It is easily distinguishable from the sibling create/get/delete spend-limit-window tools because the operation is clearly an edit.

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 gives clear operating context by instructing the agent to 'Provide window_id from get/create', which explains how to obtain the required identifier. It does not explicitly state when not to use this tool or name alternatives, but the create/get/delete sibling tools make the selection fairly obvious.

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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