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chatbot_show

Read-only

Показывает один сценарий чат-бота целиком: состояние, ревизию, сам документ сценария (scenario), его пересказ словами (description), замечания проверки и константы бота (botConstants: общие для всех сценариев бота, подставляются как {{const.имя}}; своя константа сценария с тем же именем их перекрывает; у скрытых значения нет). Звать перед правкой существующего сценария: править нужно текущий документ, а ревизию передавать в chatbot.save.

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": {
      "botId": "<botId>",
      "scenarioId": "<scenarioId>"
    },
    "name": "chatbot_show"
  }
}

Input Schema

NameRequiredDescriptionDefault
botIdYesНомер своего бота клиента (uuid) — из ответа действия chatbots.list без указания бота.
scenarioIdYesНомер сценария этого бота — из ответа действия chatbots.list.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, yet the description still adds substantial behavior: exactly which fields come back (scenario, description, validation remarks), how botConstants are substituted as {{const.имя}}, that a scenario-local constant overrides the bot-level one, and that hidden constants have no value. Since there is no output schema, this return-shape disclosure is exactly the burden the description must carry.

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?

Two sentences, front-loaded with the core purpose, followed by the pre-edit workflow rule. The parenthetical about botConstants is dense but each clause conveys distinct semantics; nothing is filler.

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?

With no output schema, the description fully compensates by enumerating the returned fields and their override/hidden semantics, and it closes the loop with the revision-passing requirement to chatbot.save. An agent has everything needed to fetch and then correctly edit a scenario.

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% and both parameters already explain their origin ('из ответа действия chatbots.list'). The description adds no further meaning about botId or scenarioId, so the baseline of 3 applies.

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?

States a specific verb and resource ('Показывает один сценарий чат-бота целиком') and immediately enumerates what the single scenario view contains (state, revision, scenario document, description, validation remarks, botConstants). This clearly separates it from chatbots_list (bot-level listing) and chatbot_save (mutation) among the siblings.

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?

Gives an explicit usage rule: call it before editing an existing scenario, edit the returned document, and pass the returned revision to chatbot.save. That names the workflow and the next sibling tool. It stops short of stating when not to call it (e.g. read-only browsing vs. editing), so it is strong rather than exhaustive.

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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