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keyso-mcp

keyso-mcp

by abukreev-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

keyso_get_report_simple_ai_answers_state

Check whether an AI report is ready for a domain, ensuring you only request data once generation is complete.

Instructions

Проверка статуса ИИ-отчёта Method: GET Path: /report/simple/ai-answers/state Возвращает текущий статус построения ИИ-отчёта для домена. Используется для проверки готовности отчёта перед запросом данных. Пример запроса: https://api.keys.so/report/simple/ai-answers/state?base=msk&domain=wildberries.ru

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "domain": "<domain>"
    },
    "name": "keyso_get_report_simple_ai_answers_state"
  }
}

Input Schema

NameRequiredDescriptionDefault
baseNoin: query
tokenNoAPI token override (fallback: KEYSO_TOKEN env)
domainYesin: query | Имя домена
base_urlNoOverride API base URL

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description must carry the full behavioral burden. It does disclose 'Method: GET', the path, and that the tool returns current status, which implies a read-only polling operation. However, it does not describe possible status values, how to interpret 'ready' vs 'in progress', or any polling/error behavior, leaving the behavioral picture incomplete.

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 description is compact and front-loaded: purpose, method, path, return value, usage context, and an example appear in a logical order. There is minor redundancy between the opening 'Проверка статуса ИИ-отчёта' and the later 'Возвращает текущий статус...', but there is no filler or irrelevant content.

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?

This is a simple state-check endpoint, yet there is no output schema and no annotations. The description gives the method, path, example, and readiness-checking purpose, but omits the actual status vocabulary an agent would need to decide whether to proceed to fetch report data. It also leaves the `base` parameter semantics vague, making the definition adequate but not fully 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 the baseline is 3. The example request `?base=msk&domain=wildberries.ru` adds some clarity by showing `base` and `domain` in context, but it does not explain what `base` values mean or how `token`/`base_url` overrides behave. Most parameter meaning still comes from 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 opens with 'Проверка статуса ИИ-отчёта' and states that it 'Возвращает текущий статус построения ИИ-отчёта для домена', giving a specific verb, resource, and scope. The explicit path `/report/simple/ai-answers/state` and the note about checking readiness before requesting data differentiate it from data-fetching siblings like `keyso_get_report_simple_organic_ai_answers`.

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 clearly states when to use this tool: 'Используется для проверки готовности отчёта перед запросом данных' (used to check report readiness before requesting data). It provides a clear triggering context, though it does not name an alternative data-fetching tool or give explicit 'when not to use' guidance.

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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