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

The annotations already establish a safe, read-only, idempotent operation, and the description adds valuable behavior: it searches names, aliases, tags, and descriptions; ignores umlauts and spelling variations; returns short summaries with BK-Score; and exposes pagination via has_more and next_offset. This goes well beyond what annotations alone provide and contains no contradictions.

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 description is well structured and front-loaded: a clear scope statement, followed by result expectations, a compact Args summary, return shape, and practical examples. The explicit 'Nicht benutzen fuer' line is efficient and earns its place; nothing in the text is wasted or redundant enough to hurt.

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?

For a search tool with rich schema annotations and an output schema, this description is fully sufficient. It covers what is searched, matching behavior, result format, pagination, usage examples, and the correct follow-up sibling tool. No critical information an agent would need to invoke or interpret the tool correctly 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 the baseline is 3, but the description adds genuinely useful meaning through concrete examples like 'Kreatin' and 'Abnehmen, bereich=experimental', clarifying how to translate user intent into query parameters. It also summarizes the purpose of offset, limit, and response_format in a way that supports selection, though much of the Args list duplicates 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 description clearly states the tool's function: searching all topics on biohackingkompakt.de across named categories, matching against names, aliases, tags, and descriptions. It also explicitly differentiates itself from the sibling bk_search_podcast and tells the agent to use bk_get_topic for full entries, making its purpose and boundaries unambiguous.

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 provides concrete usage examples, including natural-language queries mapped to parameters, and an explicit exclusion: 'Nicht benutzen fuer: eine Podcastfolge finden (dafuer bk_search_podcast)'. It also instructs the agent to follow up with bk_get_topic when complete entries are needed, which is strong routing guidance.

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