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

The annotations already establish readOnly, idempotent and non-destructive, and the description adds real behavior beyond them: the 1000-object ceiling, a measured latency figure, the explicit fail-closed scoping rule, and the crucial caveat that a missing object means "not visible" rather than "no value" (count < objects). It also states the timezone of the returned timestamps. That is exactly the context an agent cannot get from structured fields.

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 critical information (bulk current-value lookup, limits, scoping caveat) is front-loaded and dense. The tail is weaker: the keyword list ("time series, history, trend, chart, curve, sensor data, measurement") does not help an agent decide or invoke, and restating max 1000 and "both as arrays" duplicates the schema.

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 no output schema, the description supplies the response shape ({count, values[{object_udid, series_key, ts, value_float, value_str, lat, lng}]}), the semantics of count under scope filtering, and the timezone of ts. Nothing needed to call the tool correctly or interpret its result is missing.

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%, so both parameters are already documented, and the description largely restates them (array of object udids up to 1000, array of series_keys). It adds only marginal meaning, such as emphasizing that multiple series can be requested simultaneously; the UTC note refers to the response field ts, not to a parameter.

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 uses a specific verb and resource: it returns the current values of multiple time series in one call, with concrete use cases (lists, maps, vehicle fleets). The agent can tell it apart from a historical or range query, but no sibling such as onto_series_range is named or explicitly excluded, so the differentiation is implied rather than stated.

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?

It clearly says when to use it ("wo stehen alle Fahrzeuge jetzt" / lists, maps, fleets) and gives the concrete shape of a bulk lookup. It never names the alternative for historical lookups, and the trailing English keyword list ("history, trend") actually points back toward the sibling's territory, which slightly muddies the routing.

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