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

Annotations already declare read-only, idempotent, non-destructive behavior, so the bar is lower. The description still adds genuine context: the return payload is text with a link, and the notable constraint 'Quiz answers are never included' — a behavioral boundary an agent could not infer from 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?

A single sentence, front-loaded with the verb and resource, followed by the returned-content clause and the quiz-answer caveat. No filler or redundancy.

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 simple read-only tool with full schema coverage, low complexity, and no output schema, the description plus annotations give an agent enough to call it correctly. It could mention pagination or lesson-size limits, but nothing essential 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 description coverage is 100%, so both parameters (slug and the language enum) are fully documented in the schema. The description only echoes slug-based lookup and adds no syntax, format, or default detail beyond it; baseline 3 is correct.

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 and resource ('Read one RoRo Academy lesson by its slug') and enumerates the returned content (explanations, formulas, example circuits, an Academy link). This distinguishes it cleanly from search_lessons and list_learning_tracks, which don't fetch a single lesson by identifier.

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 implies usage ('Read one ... by its slug') but never states when to prefer this over search_lessons or what to do when a slug is unknown; that routing hint ('as search_lessons returns it') lives in the schema, not the description. Adequate implied context, no explicit alternatives or exclusions.

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