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

Annotations already establish readOnly, idempotent, non-destructive, closed-world, so the bar is lower, but the description still adds substance: it names the returned fields (lesson number, title, the one line to keep, an honest count), discloses the empty-result fallback, and warns that safety routing runs first. That safety pre-emption is a behavioral trait not encoded anywhere in the structured fields.

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?

Four sentences, front-loaded with the verb and the returned fields, then the fallback and the get_lesson contrast. The parenthetical list of topic examples plus "and the rest of the bank's own topic words" runs a little long, but every sentence carries information an agent needs.

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?

There is no output schema, so the description correctly spends words on return contents and the empty-result shape, and it flags the safety override. For a one-parameter read tool with full annotation coverage, nothing needed to call it 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% and describes the single topic parameter, so the baseline is 3. The description adds that valid topics are drawn from "the bank's own topic words" rather than free text, which meaningfully constrains how an agent should pick a value beyond the schema's loose "a topic in a word or two."

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?

"Lists the written Dadiosity lessons filed under a topic" gives a specific verb (lists) and resource (lessons), and the examples (tantrums, listening, mornings, hitting, bedtime) pin down the topic bank. It also explicitly separates itself from get_lesson with "It lists only; get_lesson reads one in full."

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 covers the primary case, the empty case ("When nothing is filed under the topic, it says so and lists topics that do exist"), and the alternative tool for full content (get_lesson). It also routes medical or diagnostic topics to the safety answer instead of a list, which is a real usage carve-out an agent could not infer.

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