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Qusto

vk-ads-mcp

by Qusto

get_rate_limits

Read-onlyIdempotent

Check remaining VK Ads API quota before making requests, combining live throttling data with cached rate-limit headers to diagnose HTTP 429 errors.

Instructions

Report remaining VK Ads API quota for diagnostics.

Combines two sources of throttling information:

  • A live GET /throttling.json call returning the API's current view of remaining requests per second, per hour, and per day (throttling).

  • The last X-RateLimit-* header values observed on any prior request, cached on the shared client (last_seen).

Use this to check how much API budget is left before issuing further listing or statistics requests, or to debug HTTP 429 rate-limit errors.

Returns: A dict with two keys:

* ``throttling``: the decoded ``/throttling.json`` body (remaining and
  limit values for rps/hourly/daily quotas, as returned by the API).
* ``last_seen``: the most recent rate-limit header values observed by
  the client (``rps_remaining``, ``hourly_remaining``,
  ``daily_remaining``); values are ``None`` until a request has run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint true. The description adds context about combining two sources (live call and cached headers) and confirms it's a safe diagnostic operation, adding value beyond annotations.

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 well-structured: a concise summary, bullet points explaining two sources, and a usage recommendation. No unnecessary words; every sentence adds value.

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

Completeness5/5

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

For a zero-parameter diagnostic tool, the description fully explains what it does, the data sources, the return format, and when to use it. No gaps given the simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has no parameters (0 params, 100% coverage), so baseline is 4. The description does not need to add parameter info as there are none.

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 it reports remaining VK Ads API quota for diagnostics, naming specific data sources (live throttling call and cached headers). It distinguishes itself from siblings by focusing on quota diagnostics rather than data retrieval.

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 explicitly says 'Use this to check how much API budget is left before issuing further listing or statistics requests, or to debug HTTP 429 rate-limit errors.' It provides clear context but does not explicitly exclude other uses or mention alternatives.

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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