lesson_validate

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses the categories of validation performed and the default 'all lessons' scope, but it does not clarify permissions, whether validation is purely read-only, or how results are returned.

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 compact clauses, front-loads the purpose, and uses a parenthetical to list concrete validation examples without wasted text. Every part contributes useful information.

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 two-parameter validation tool with no output schema and no annotations, the description covers the core purpose and one parameter's default behavior. It remains incomplete because course_dir is unexplained and the result/error behavior is not described.

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%, so the description must compensate for both parameters. It explains the lesson_id semantics ('비우면 전체' / empty means all) but says nothing about course_dir, leaving one of two parameters undocumented.

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 ('검사합니다' / validates) and resource ('레슨 형식' / lesson format), and enumerates concrete checks such as missing code lines, unknown op/widget, and hard-to-read words. It is clear what the tool does, though it does not explicitly contrast itself with siblings like code_verify or course_status.

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?

It gives one useful usage rule: if lesson_id is empty, all lessons are validated. However, it does not say when to use this tool versus related siblings such as code_verify or course_status, so broader usage guidance is only implied.

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