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niyogi

chatgpt-ads-manager-mcp

by niyogi

get_ad_account_spend_limit_windows

Retrieve spend limit windows for an ad account, showing inclusive start and exclusive end times in ascending order. Use this data to audit current budget caps or plan future spending limits.

Instructions

View spend limit windows (inclusive start, exclusive end, ordered by start ascending). Use to audit or plan budget caps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ad_account_idNoOptional ad account ID override.
Behavior4/5

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

With no annotations, the description is the sole source of safety and behavior info; the word 'View' conveys read-only, and the interval/ordering semantics tell the agent exactly how the result set is bounded. It doesn't cover pagination or what happens when none exist, but for a simple read tool the disclosed semantics are above par.

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?

Two sentences, no fluff: the first packages the core behavior and two precise semantic constraints, the second gives the practical use case. Information is front-loaded and every word carries weight.

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?

For a one-optional-param read-only tool, the description is nearly complete: it says what the tool returns conceptually, how the windows are ordered, and when to use it. The only notable gap is the lack of any description of the returned window fields, but with no output schema and a self-explanatory resource name this is a minor 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 coverage is 100%—the parameter ad_account_id has a description ('Optional ad account ID override')—so by the rubric baseline is 3. The tool description adds no extra param meaning, so it doesn't rise above the baseline.

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 uses a specific verb-resource pairing ('View spend limit windows') and adds distinguishing details (inclusive/exclusive bounds, ascending order) that set it apart from the create/update/delete siblings on the same resource. The name alone could be ambiguous, but the description pins down the exact read operation.

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?

It states the intended use cases—'audit or plan budget caps'—which gives an agent a clear trigger for choosing this tool. It does not name alternatives or exclusions, so it lacks full when-not guidance; still, the context is clear.

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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