list_dialogs

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

With no annotations provided, the description carries the behavioral disclosure burden. It does disclose the filtering behavior: chat_type filters to all, channel, group (including supergroups), or user. However, it does not mention pagination, ordering, authentication, or other runtime behavior, leaving a moderate gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with no filler; the verb-resource statement is front-loaded and the parameter detail follows directly. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter list operation with an output schema, the description covers both the operation and filter semantics adequately. A small gap remains in not mentioning when to prefer this over sibling message/channel tools, but the low complexity and existing output schema keep it largely complete.

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

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

Schema description coverage is 0%, but the description fully compensates for the single parameter by enumerating the accepted chat_type values and clarifying that "group" includes supergroups. This is exactly the semantic guidance the schema lacks.

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

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

The description opens with the specific verb-resource pair "List Telegram dialogs", which clearly identifies what the tool does. It does not explicitly compare itself to siblings like get_messages or get_channel_info, so it stops short of full differentiation.

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

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

Usage context is implied by "List Telegram dialogs" and the chat_type filtering sentence, but no when-to-use or when-not-to-use guidance is provided. The agent must infer that this is the right tool for enumerating dialogs rather than messages or channel info.

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