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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description usefully adds the return shape (URL, source, matching text) and a content-policy note that results are GIS-safe and non-diagnostic, but says nothing about result limits, ranking, or empty-result behavior.

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?

Three sentences, front-loaded with what is searched and over what corpus, then return fields, then policy. The final GIS-safe sentence is not filler because it tells the agent how to present results, though it could be tightened.

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 single-parameter read-only search with no output schema, the description is nearly sufficient: corpus, example queries, and return fields are all covered. The remaining gaps are operational details such as result count limits and whether matching is keyword or semantic.

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?

With a single parameter at 100% schema coverage, the schema already documents 'pytanie' as a search phrase or question. The example queries give some hints about phrasing (natural-language questions rather than keywords), but no syntax, length, or query-construction guidance beyond what the schema states.

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 names a specific verb ('searches') and an explicit corpus: the Aloha Fungi blog, PDP content, and species guides. Listing the content sources separates it from the product-search siblings, but it never acknowledges the closest-sounding sibling (zapytaj_wiedze / 'ask knowledge'), so the boundary with that tool is left to inference.

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 three example queries imply the intended use (natural-language questions about dosing, benefits, contraindications), which is clear enough context. However, there are no explicit when-to-use/when-not-to-use rules and no named alternative for product lookups or the Q&A-style sibling, so routing depends on the agent's own inference.

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