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

Annotations already cover safety (readOnlyHint=true, openWorldHint=false), yet the description still contributes real context: the response shape, the presence of answer keys with a reveal gating rule, and the 'No sign-in needed' auth note. It stops short of stating what happens for an unknown topic, but adds genuine value beyond 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?

A single front-loaded sentence with a colon-delimited inventory; every clause (contents, key reveal order, no auth) carries information. Nothing is repeated from the name or title.

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?

With no output schema, the description accepts responsibility for describing return contents and does so thoroughly, plus auth and key-reveal behavior. Only the failure mode (invalid topic/examId) is left unaddressed.

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 description coverage is 100% and both parameters (examId, topic) are already documented as slugs from list_learn_topics. The description adds no format or relationship detail beyond what the schema provides, so the baseline 3 applies.

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 resource ('One /learn concept page') and scope ('in full'), then enumerates exactly what makes it up: answer, sections, exam traps, vendor docs, related topics, practice questions. This cleanly separates it from list_learn_topics (listing) and learn_question (single-question interaction).

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 implied — fetch this when you need a whole concept page rather than the topic list or a single question — but no alternative sibling is named and no exclusion is stated. The only explicit guidance is the practice-question reveal cue ('reveal after the person picks').

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