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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuine context beyond that by stating the corpus is free lessons and enumerating the returned fields (title, page, course, summary, quiz), which matters since there is no output schema.

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?

Two sentences, front-loaded with the verb and resource, with the examples and return fields packed in without filler. Every clause earns its place.

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 two-parameter search tool with no output schema, the description covers purpose, query style, and return fields adequately. It says nothing about ranking/relevance behavior or how results relate to the full lesson reachable via get_lesson, a minor but real gap.

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 both parameters are documented, giving a baseline of 3. The description goes further by showing that the query can be a natural-language question rather than just a keyword, which is real semantic value not conveyed by the schema's bare "A topic or a question."

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+resource ("Search ... free gemology lessons") and illustrates it with three concrete example queries, so the tool's function is unmistakable. It doesn't explicitly contrast itself with the siblings get_lesson or explain_term, but 'search' vs 'get'/'explain' is largely self-evident.

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 query examples imply the right usage context (a topical question you want lessons on), which is helpful guidance. However, there is no explicit when-to-use/when-not or pointer to get_lesson for fetching a full lesson, so an agent must infer the boundary with siblings.

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