get_snapshot

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

With no annotations, the description carries the full behavioral burden and supplies almost none of it. It says nothing about authentication/scope requirements, the return shape, rate limits, or whether 'shallow' changes cost/behavior. Only the word 'broad' hints at scope.

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?

It is a single front-loaded sentence with no padding, which is structurally clean, but it is under-specified rather than genuinely concise. Brevity here costs clarity.

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 tool with three undocumented parameters, no annotations, and no output schema, the description is grossly incomplete. It omits what is returned, what the parameters mean, and when the tool should be used, giving the agent almost nothing to act on.

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% and there are three parameters (course, shallow, since_hours), yet the description mentions none of them. It does not explain what 'shallow' toggles or what 'since_hours' scopes, so it fails to compensate for the total coverage gap.

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 pairs a verb ('Return') with a resource ('snapshot'), so the basic action is clear, but 'broad AI-oriented academic snapshot' is vague jargon that never states what data the snapshot actually contains or how it relates to the many sibling readers (get_grades, get_upcoming_due, get_announcements, etc.). An agent cannot tell what it will get or why this differs from the specific tools.

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?

There is no explicit when-to-use guidance. 'broad' weakly implies it aggregates many categories, but nothing tells the agent when to prefer this over the specific sibling tools or when to avoid it. The routing decision is left entirely to inference.

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