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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuinely useful interpretive context beyond that — that prices carry sources, photos carry author and license, and that price and city are explicitly excluded from the score — which prevents misreading the returned score. No mention of auth needs or behavior when a slug is not found.

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?

Front-loaded with the core claim ("Всё об одной модели") followed by the content inventory and the usage trigger, so an agent can stop reading early. The full Russian list is then repeated as an English summary, which is helpful for cross-lingual matching but adds duplication length.

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?

An output schema exists, so return values need not be explained, and the description still covers scope, usage trigger, and the important scoring caveat. What remains uncovered is the failure path for an unrecognized slug and explicit sibling routing, both minor for a single-parameter read tool.

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 coverage is 100% and the single `slug` parameter is already documented in the schema as accepting either an identifier or a free-form model name. The description adds nothing about the parameter, which is acceptable at full coverage but earns only the baseline.

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 a concrete verb+resource ("full card of one model") and enumerates exactly what the card contains: per-channel prices with sources, range figures, battery/charging, a four-part score, known issues, sources, and credited photos. This makes it clearly distinct from list/aggregate siblings like search_models or compare_models, though it never names those siblings.

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?

The line "Звать, когда спрашивают про конкретную машину" gives a clear trigger condition that separates it from search/compare workflows. It stops short of naming alternatives or stating the prerequisite (e.g., resolve a slug via search_models first), so the routing is implied rather than explicit.

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