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draiqw

telegram-mcp

by draiqw

tg_mentions

Fetch unread Telegram mentions and reactions to your messages. Control output with kind (mentions/reactions) and limit parameters.

Instructions

Unread messages that mention you, or unread reactions to your messages.

Args: limit: how many to return. kind: "mentions" (default) — where you were called out; "reactions" — messages of yours someone reacted to and you have not seen the reaction yet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNomentions
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

The description explains that only unread mentions/reactions are returned and clarifies the 'reactions' mode, but does not state whether fetching this data marks items as read or has other side effects. With no annotations provided, this missing side-effect disclosure is a notable gap, though the tool appears to be read-only.

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 concise and well-structured, leading with the purpose and following with a clean Args list. Every sentence adds value and there is no redundant 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?

For a simple tool with two optional parameters and an output schema, the description covers the essential behavior and parameter semantics. Minor gaps include not explicitly stating the scope (all chats) or whether results are ordered, but overall it is sufficiently complete.

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

Parameters5/5

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

The description fully explains both parameters in depth: 'limit' is defined as 'how many to return' and 'kind' has explicit meanings for 'mentions' and 'reactions' with default behavior. Since the schema contains no descriptions, this completely compensates for the 0% schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool's purpose as retrieving unread messages that mention the user or unread reactions to their messages. It distinguishes mentions from reactions, but lacks an explicit verb like 'get' or 'list', making it slightly less direct than ideal.

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 provides clear context by explaining the two 'kind' options and their meanings, which implicitly tells the user when to use each mode. However, it does not explicitly discuss alternatives or exclusions relative to other tools such as tg_unread or tg_activity.

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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