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

Annotations already mark it read-only, so the description adds real value: it discloses data provenance (Reddit and other monitored communities), the aggregate-only scope ("in total"), and an access restriction — the underlying requests are shared only with TutorPing tutors. It doesn't cover freshness/latency or update cadence, but the disclosure is well above the annotation baseline.

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 tight sentences that lead with the core metric definition, then add usage context and an access caveat. Near-zero waste, though "in total" is slightly redundant with the opening "How many people."

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?

With no output schema, the description correctly carries the return-value burden by framing the result as a total count. Combined with the data-source and access-restriction notes, an agent has enough to call it correctly for a simple two-parameter tool.

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 50%: subject is documented with examples, while days relies on its default/min/max constraints. The description reinforces the subject concept and the "recently" window but gives no detail on the days parameter's meaning, so it only marginally compensates for the 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?

States a specific resource and metric: a count of recent tutor requests for a given subject, sourced from Reddit and monitored communities. An agent can distinguish this aggregate-demand tool from siblings like search_tutors or get_tutor, though no sibling is named explicitly.

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?

"Useful for tutors deciding whether there is demand for their subject" implies the use case but never states when to use this versus alternatives (search_tutors, ask_tutorping, how_to_get_leads) or any prerequisite. Guidance is present but left to inference.

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