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

Annotations already declare readOnlyHint/idempotentHint/openWorldHint, so the safety profile is covered. The description adds real behavioral context beyond them: numbers are computed live from the current inventory and may diverge from the published 2026 report (Stand 15.10.2026, 494 Mittel), and it notes that report is separately available as page/PDF/CSV under report/2026. That is a meaningful caveat an agent must not misreport.

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?

Purpose and metric scope are front-loaded in the first sentence, and the subsequent sentences (example questions, published-report caveat) each carry information an agent needs. The opening sentence is long and list-heavy, but nothing is padding.

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-shape explanation is rightly omitted. For a read-only aggregation tool the description covers scope, available category slices, and the live-vs-published discrepancy, leaving little an agent needs uncertain.

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 100%, so the schema already documents all three parameters, enum values and defaults; baseline is 3. The description adds only a small amount beyond it, notably that the examples are the best-studied ones first ("die am besten untersuchten zuerst"), which is genuine but limited added meaning.

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 specific resource (die Kennzahlen des Biohacking-Reports von biohackingkompakt.de) and what is computed (live aus dem aktuellen Bestand), then enumerates the exact metric labels (gut belegt, mit Einschränkungen belegt, dünn belegt, nie am Menschen untersucht, weit vor der Evidenz beworben) and the five Bereiche. That level of specificity makes it unmistakable as an aggregate-statistics tool rather than a per-topic getter like bk_get_topic.

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?

Gives concrete example questions it answers ("Wie viel im Biohacking ist überhaupt belegt?", "Wie steht es um Peptide insgesamt?"), which tells the agent when to reach for it. It does not name an alternative tool or state when not to use it, so it stops short of full routing guidance.

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