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LoneVertex

Telegram MCP — Next Generation

Retrieve Dialogs and Recent Chats List

get_chats
Read-onlyIdempotent

Retrieve active dialogs and recent conversation summaries, including last message and unread count, for an overview of recent chat activity. Read-only.

Instructions

Retrieve active dialogs and recent conversation summaries including last message and unread count. Use for overview of recent chat activity. To search or list all chats comprehensively, use list_chats. Read-only operation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-indexed page number for paginated result sets.
accountNoOptional account label for multi-account environments. If omitted in single-mode, the default account is used. In multi-mode without an account, read-only tools fan out across all configured accounts.
page_sizeNoMaximum number of items to return per page (typically 10 to 50).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.1.1

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is fully covered by structured data. The description's 'Read-only operation' merely restates the annotation, and the return-content note ('last message and unread count') overlaps with the existing output schema. It adds little behavioral context beyond annotations, so a baseline 3 is appropriate.

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?

Three tight sentences that front-load the resource and scope before the routing note. The final 'Read-only operation' sentence is redundant with the readOnlyHint annotation and is the only wasted text.

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?

Given the output schema exists, the description needn't explain return values, and it correctly covers purpose, scope, and sibling routing. It is essentially complete for a read-only list tool, with only minor redundancy rather than a substantive gap.

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% with all three parameters (page, account, page_size) fully documented in the schema itself, including the multi-account fan-out behavior. The description adds no parameter-level detail, so the baseline 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+resource ('retrieve active dialogs and recent conversation summaries') and immediately differentiates itself from the sibling list_chats for comprehensive listing. An agent can distinguish it from list_chats, get_chat, and get_full_chat without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit context ('Use for overview of recent chat activity') and names the alternative tool with the condition that selects it ('To search or list all chats comprehensively, use `list_chats`'). This is the when/when-not/alternative pattern done well.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.