get_notebook_exercises

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

With no annotations, description carries burden. It discloses return format (markdown and code), what is skipped, and the kind parameter with default. Lacks mention of error behavior or idempotency, but these are minor for a fetch 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?

Three sentences front-load the purpose, then add usage guidance and parameter info. No wasted words; every sentence adds value.

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 low complexity (2 params, no nested objects, has output schema), description covers purpose, parameter, usage, and return. No gaps for effective use.

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 0% description coverage. Description adds meaning for kind parameter by listing possible values and default. module_id is self-explanatory from name, so minimal gap remains.

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 verb 'Fetch' and resource 'exercise cells from a module's notebook' clearly state the action and object. It distinguishes from sibling get_notebook_content by specifying what it skips (expository text, imports, solutions) and what it returns (prompt and skeleton code).

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?

Explicitly states 'Prefer this over get_notebook_content when helping a student with an exercise', providing a clear usage context and exclusion of alternatives. No additional when-not advice needed.

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