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

With no annotations, the description carries the full behavioral burden. It does disclose one real trait — output order follows the order of the given values — which is non-obvious and valuable. But it omits that this is a read-only lookup, what happens with an unknown column or fewer than 2 / more than 10 values, and how many rows are returned.

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?

A single compact sentence front-loads the resource and scope, then appends the usage hint after a dash. Every clause earns its place, but the sentence is grammatically incomplete (no verb), which slightly hurts immediate parseability.

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?

No output schema, no annotations, and zero schema description coverage for two required parameters — the description should be doing much more work. It never says what a returned row contains, how many rows come back, or how errors are surfaced, leaving an agent to guess at the response shape.

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%, so the description must compensate, and it does explain the column/values relationship and that result order mirrors input order. It still leaves the matching semantics opaque (exact vs partial string match, case sensitivity) and never mentions the 2–10 item constraint enforced by the schema.

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 fragment states the resource (rows of the Wärmepumpe Kosten Europa dataset) and the filter semantics (column matches any of the given values, order preserved), so an agent can infer it fetches rows for comparison. However, it is grammatically verbless and never distinguishes itself from siblings like dataset_row, dataset_search, or dataset_top, which also return rows.

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 trailing clause 'for "X vs Y" questions' implies the usage context (side-by-side comparison of multiple entities), which is genuinely useful routing information. But no alternative tool is named, no when-not-to-use is given, and it does not say how this differs from dataset_search for the same comparison need.

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