Sends up to 50 results as a response to a Telegram inline query, letting bots return matching content with optional caching and personalization.
Send answers to an inline query. Max 50 results per query.
| Name | Required | Description | Default |
|---|---|---|---|
| button | No | ||
| results | No | ||
| cache_time | No | ||
| is_personal | No | ||
| next_offset | No | ||
| inline_query_id | Yes |
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already disclose readOnlyHint=false and destructiveHint=false, covering the base safety profile. The description adds the 'Max 50 results' limit, which is a useful behavioral constraint. However, it does not elaborate on side effects, caching, or error handling, so the additional context is limited but not absent.
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?
The description is two short, direct sentences with no filler. It front-loads the primary action ('Send answers to an inline query') and then states the key limitation, achieving maximum clarity in minimal space.
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?
With six parameters and no output schema, the description is too sparse to cover the tool's complexity. It omits essential details about result formatting, parameter structure, and when it is appropriate to invoke this method, leaving substantial gaps for an AI agent.
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% for six parameters, so the description must compensate. It only vaguely references 'results' via the maximum count and fails to explain inline_query_id, cache_time, is_personal, next_offset, or button. This leaves the agent with minimal understanding of how to populate the parameters.
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 clearly identifies the action ('Send answers') and specific resource ('inline query'), which distinguishes it from sibling tools like answer_callback_query or answer_shipping_query. It also adds a key constraint ('Max 50 results per query'), making the purpose unambiguous and well-scoped.
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?
No guidance is provided on when to use this tool versus other answer_* tools. The description does not mention alternatives, conditions, or prerequisites, leaving the agent to infer selection solely from the tool name and the phrase 'inline query'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.