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OrrBin

Telegram MCP Server

by OrrBin

search_chats

Find Telegram chats by searching their title or username, with options to limit the number of results.

Instructions

Search for chats by title or username

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results to return (default: 20, max: 100)
queryYesSearch query to find chats by title
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states the basic search function and does not mention return format, pagination, error handling, authentication needs, or limitations. For instance, it does not clarify whether the search matches partial titles, how many results are returned by default, or if there are rate limits. This is a minimal disclosure that leaves significant gaps.

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 a single, efficient sentence with no redundant words or filler. It states the essential action and criteria in a compact format, earning every word. There is no unnecessary elaboration, and the structure is perfectly appropriate for the tool's simplicity.

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

Completeness3/5

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

The tool is relatively simple with two parameters and no output schema. The schema covers the parameters well, and the description provides a clear purpose. However, the absence of annotations and output schema means the description should compensate by explaining return values or behavioral details, which it does not. For a search tool, this is a moderate gap—adequate for basic understanding but lacking crucial context like result structure or edge cases.

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

Parameters4/5

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

The schema covers both parameters (query and limit) with descriptions, giving a baseline of 3. The description adds meaningful extra semantics by stating that search can be performed 'by title or username,' whereas the schema's query description only mentions 'title.' This additional insight about the username criterion is valuable, even though it creates a slight inconsistency with the schema. The added context justifies a score above baseline.

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 states the tool's function: 'Search for chats by title or username.' It specifies the action (search) and resource (chats), and the criteria (title or username) makes it distinct from siblings like list_chats or get_chat_info. However, it does not explicitly differentiate from search_messages or provide a comparison, so it lacks the explicit sibling distinction seen in high-scoring examples.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. The description does not mention any prerequisites, exclusions, or scenarios where another tool (e.g., list_chats or search_messages) would be more appropriate. The phrase 'Search for chats' implies a general use case but offers no explicit when-to-use or when-not-to-use direction.

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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