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LoneVertex

Telegram MCP — Next Generation

Search Messages Across All Public Chats

search_global
Read-onlyIdempotent

Search message text across all joined Telegram dialogs and public channels when the target chat is unknown. Find messages globally by keyword without specifying a chat.

Instructions

Search for message text across all joined dialogs and public channels globally. Use when the target chat is unknown. If the chat is known, prefer search_messages for faster scoped results.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-indexed page number for paginated result sets.
queryYesSearch text string or keywords to match against messages, contacts, or entities.
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

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds real value beyond that by disclosing the breadth of the scan (all joined dialogs plus public channels) and the cost trade-off versus the scoped sibling. It stops short of describing result ordering, pagination limits, or multi-account fan-out behavior.

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?

Three short sentences, front-loaded with the scope before the routing advice. Every sentence earns its place: what it searches, when to use it, and which alternative to prefer.

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?

An output schema exists, so return values need no explanation, and the annotations carry the safety semantics. Combined with full parameter documentation, the description supplies everything else an agent needs to select and call this search tool correctly.

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 all four parameters (query, page, page_size, account) are already documented in the schema. The description adds no syntax, matching, or filtering semantics beyond what the schema states, which is the baseline 3 case.

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 (search message text) with an explicit scope (all joined dialogs and public channels globally). It also names the sibling it is not — `search_messages` — so an agent can distinguish the two without opening either 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 an explicit when-to-use condition ('Use when the target chat is unknown') and a when-not condition with a named alternative ('If the chat is known, prefer `search_messages` for faster scoped results'). Nothing is left to inference.

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