academy_next_lesson

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

No annotations provided, so description carries burden. It mentions requires sign-in but does not disclose other behavioral traits like output format, side effects, or rate limits. Could be more transparent, but enough for a simple recommendation tool.

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?

One sentence with parenthetical note, front-loaded with action, zero waste. Efficient and clear.

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 no output schema and no annotations, description covers main purpose and the rule, but lacks details on what the output looks like (lesson object? ID?), or how sign-in plays in. Still, for a simple tool, it's adequate but could mention response format.

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 has only one optional locale param with enum, but description doesn't explain its meaning or default behavior. With 0% schema description coverage, description compensates partially by indicating the recommendation logic, but does not add param-specific meaning. Since locale is optional and has enum, schema already provides choices, but default behavior missing.

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?

Description states a clear purpose: recommend next lesson based on progress, with a specific rule (first incomplete lesson in lowest level). It clearly distinguishes from siblings like academy_lessons or academy_lesson by focusing on recommendation logic.

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?

Implies usage: call this to get recommended next lesson. Does not explicitly state when to use over alternatives, but the rule about progress and levels provides context. No exclusion or alternative mention.

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