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

Annotations already declare it a safe, idempotent read, and the description still adds material behavior: results link to their source, recipes lacking nutrition are excluded when a nutrition filter is set, and there is a default rating/review floor with documented escape hatches (-1 disables). Those exclusion and default rules change whether an agent finds results and are not in the annotations.

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?

Five sentences, front-loaded with the purpose and use cases, then filter behavior and defaults. The parenthetical nutrition list is nearly a schema restatement, but overall there is little waste and the important exclusion/default rules are easy to find.

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?

Thirteen parameters at 100% schema coverage plus an output schema mean the description need not explain return values, and it does not. It still covers the decision-critical unknowns: default thresholds, how to disable them, and the nutrition-filter exclusion behavior. Nothing an agent needs to call this 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 3 is the baseline, but the description adds semantics the schema lacks: which filters exist in prose, that nutrition values are per-serving as reported by the source, and that min_rating/min_reviews have non-obvious defaults plus the -1 disable mechanism. That is genuine meaning beyond the schema descriptions.

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 verb (search) plus resource (recipes) and adds scope that differentiates it: bounded by what-to-cook questions, human-rated, with source linking. Sibling names like find_by_ingredients and get_recipe make the differentiation concrete once the description anchors to query-based discovery rather than ingredient matching or retrieval by id.

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?

Enumerates concrete use cases (dinner tonight, cooking for guests, quick weeknight meal, protein/calorie targets), which effectively tells the agent when this tool applies. It does not explicitly contrast against sibling find_by_ingredients or get_recipe, so the alternative-selection guidance is implicit rather than stated.

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