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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to repeat those. It adds behavioral value by specifying that the transcript is only returned for free lessons and listing the full set of returned fields, which is context not present in the annotations. This goes beyond baseline and provides agents with concrete expectations about the response contents.

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?

The description is two sentences with no filler. The first sentence front-loads the primary purpose and enumerates return fields efficiently, while the second sentence gives actionable usage guidance. Every word earns its place, making it concise and easy to parse for an agent.

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 single-resource getter with one parameter, the description is thorough: it lists all returned fields, notes the conditional transcript for free lessons, provides usage context, and states the source of the identifier. The annotations already cover safety and idempotency, and there is no output schema, so the description fully equips an agent to call the tool correctly and interpret the result.

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?

The schema already provides 100% coverage for the single parameter lesson_id, including its source ('from search_lessons or get_course_outline'). The tool description reinforces the link to search_lessons but does not add any new semantic detail beyond what the schema already states. Per the calibration rule, baseline 3 is appropriate when the schema carries the parameter documentation burden.

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?

The description uses a specific verb ('Returns') with a specific resource ('public details of one lesson') and enumerates the exact fields returned, which clearly distinguishes it from siblings like search_lessons and get_course_outline. It also explicitly positions it as the follow-up to search_lessons, making its unique role unambiguous.

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 gives a clear usage context: 'Use it after search_lessons to answer questions about a specific lesson.' It tells the agent when to call this tool and implies it is for detail retrieval after a search. However, it does not explicitly state when not to use alternatives like get_course_outline, so it stops just short of a 5.

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