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

Annotations cover the safety profile (readOnly, idempotent, non-destructive), and the description adds genuinely useful context beyond them: the tool only hands back a link and a message, and 'Nothing is sent for the user — they send it themselves' clarifies the human-in-the-loop step. It does not mention limits such as one sample per user or what happens after the Telegram message is sent.

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 sentences with no filler, and the key caveat about who sends the message is placed last as a distinct clarification. The phrasing is slightly run-on but every clause carries information.

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 two-parameter, read-only tool with no output schema, the description discloses what comes back (a link and a message) and the user action required. Missing only edge cases such as sample eligibility or rate limits.

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?

Both parameters are fully documented in the schema (100% coverage) with detailed enum meanings, so the schema carries the load. The description only restates them as 'your country, your filter' and adds no format or semantics beyond that.

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?

States the concrete deliverable — a Telegram link plus the message to send — for obtaining a free 200-number sample, which separates it from an ordering flow. It does not name the siblings get_catalog or get_quote, so an agent must infer the boundary from 'to test before ordering' rather than an explicit contrast.

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?

'to test before ordering' gives a clear usage context: use this before committing to a purchase. It stops short of explicit alternatives (e.g. 'use get_quote to price a real order'), so the when-not guidance is implied rather than stated.

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