lesson_get

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

No annotations are provided, so the description carries full burden. It states the tool returns the full body, indicating a read operation with no side effects. However, it does not disclose any behavioral details such as authentication requirements or rate limits. The presence of an output schema partially mitigates this.

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 redundant information. The first sentence states the action, the second provides a concrete use case, making it efficient and front-loaded.

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?

Given the tool has a single required parameter, an output schema, and is a simple read operation, the description adequately covers its purpose and usage context. It could mention potential edge cases or return format, but the output schema likely fills that 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 description coverage is 0%, but the description only adds 'by slug' to explain the required parameter. It does not clarify what a slug is, its format, or constraints, leaving the agent to infer from the schema property name.

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 clearly states the tool returns the full body of a lesson by slug, using specific verb and resource. It distinguishes itself from lesson_list by noting it is for reading content in full after listing.

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 explicitly ties usage to lesson_list, suggesting it is appropriate when a lesson slug has been surfaced. However, it does not mention other sibling tools like lesson_remove or lesson_append.

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