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

Beyond the readOnly/idempotent annotations, the description discloses that the list excludes promotional reports, that total reflects the filtered list, and that promotional reports appear as ads on the website. It also flags the epistemic limitation that a report is a single observation, not a proof.

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 main behavior is front-loaded and followed by two purposeful caveats, then structured Args and Returns sections. The Args block is somewhat redundant with the schema, but it is compact and does not waste sentences.

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?

The definition is complete for this listing tool: it states the content, filtering behavior, pagination fields, and return item shape, and it names the relevant sibling tool for efficacy. The output schema and annotations cover the remaining structured details.

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?

The input schema already describes all five parameters at 100% coverage, so the description's Args section does not add much semantic value. It repeats optionality and defaults without adding new meaning beyond what the schema provides.

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 opens with a specific verb and resource ('Listet die Erfahrungsberichte von biohackingkompakt.de') and defines the list's content (Selbstversuche, recherchierte Berichte, Dauer, Dosierung, Fazit). It differentiates this listing from the efficacy-oriented BK-Score tool by explicitly stating that a report is only a single observation and not proof.

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 description gives explicit guidance not to treat Erfahrungsberichte as evidence of efficacy and points to bk_get_topic for the BK-Score. It also explains the list is filtered to exclude partner-program/rabattcode reports and that total refers to this filtered list, so an agent knows how to interpret results.

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