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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds the non-obvious capability of returning a 'missing-grade-needed forecast', which is genuine behavioral value, but it says nothing about validation (e.g., coefficient/grades length mismatch) or error behavior.

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?

Four short sentences, front-loaded with the core action before usage, inputs, and the cross-reference. Efficient overall, though the trailing bundle pointer is slightly tangential to calling the tool.

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?

Output schema exists so return values need no elaboration, and annotations cover the safety profile; the description still adds inputs and the forecast capability. The main gap is failing to position itself against the near-identical calculate_average and calculate_grade_needed siblings.

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 100%, so the schema fully documents both parameters. The description merely restates them ('grades list, optional weights/coefficients') without adding format or constraint meaning, which is the correct baseline when the schema does the heavy lifting.

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 verb+resource ('Compute simple or weighted grade average') and scopes it to school report cards. It distinguishes itself somewhat from the generic calculate_average sibling by the 'grade' qualifier, but never names calculate_average or calculate_grade_needed explicitly, so sibling disambiguation is left to inference.

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?

Provides an implied usage context ('Use for school report cards') but no when-not guidance and no named alternatives. With siblings like calculate_average and calculate_grade_needed in the same domain, the agent must guess which tool applies to a bare averaging request.

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