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

Annotations already declare read-only, idempotent, open-world behavior, so the safety bar is low and the description adds real substance: it discloses the breadth of returned content, that cultures are cross-matched to a shop database with price, price per liter and card link, that the author's make-log is conditional ("a gdy jest"), and that the hub forwards the query to an external server. It does not describe behavior for an unrecognized cheese name, which is the main remaining gap.

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 is front-loaded in the opening clause and every subsequent phrase enumerates actual returned content rather than filler. It is one long run-on sentence with a dense comma-separated list, which is harder to scan than it needs to be, but no sentence is wasted.

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 exists, so the description must carry the return-value burden, and it does so thoroughly, enumerating the recipe sections, the matched culture records with price fields, and the optional author log. Only the not-found or ambiguous-name case is unaddressed for a single-parameter lookup tool.

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% and the single parameter is already documented as "Nazwa sera albo id z wyników szukaj_przepisow". The description adds only concrete example values ("mozzarella", "gouda", "ser topiony") and implies name-matching tolerance, which is a marginal gain over 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?

Names a specific resource and scope: the full step-by-step recipe for one specific cheese, retrievable by name or id. The list of what the recipe contains (milk, starter culture, coagulant, dosage, temperature/time steps, salting, aging, tips, author's make-log) plus the matched culture offers clearly sets it apart from the sibling search tools.

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?

Usage is only implied: the tool takes a specific cheese name or id, so an agent must already have an identifier, which in practice means calling szukaj_przepisow first. The description never says that explicitly, nor does it state what to do if the cheese is unknown, so the routing to siblings is left to inference from the parameter schema.

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