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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world). The description adds meaningful domain behavior beyond annotations: rows without a score count as open, and the result includes graded/open weight and an optional target-grade what-if calculation.

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?

The description is front-loaded with the primary use case, then supported by concrete examples and an exclusion. It is dense but each sentence contributes relevant information; the only minor issue is the long middle sentence packing multiple return details.

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?

An output schema exists, so return-value explanation is not strictly required, but the description still helpfully summarizes outputs. For a nested-row calculation tool, it covers row semantics and target-grade behavior well; scale behavior remains implicit.

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 coverage is 67%, and the description adds useful semantics: score may be percent, fraction, or letter; omitted scores mean ungraded; target_grade optionally computes what the open portion must average. It does not explain the scale enum, but the row-level semantics are well clarified.

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 states a specific calculation (weighted course grade from weighted categories) and gives a concrete example (homework 20%, tests 50%, final 30%). It distinguishes itself from single-question exam tools, though it does not name any sibling tool 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?

It provides a clear 'use this when' trigger and an explicit exclusion ('Do not use it for a single final-exam question without categories'). It does not name alternative sibling tools, but the boundary condition is sufficient for routing.

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