calculate_grade_average

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states that the tool returns a weighted average and a missing-grade-needed forecast, and outlines the inputs (grades list, optional weights). This is sufficient for a non-destructive calculation tool, though it could mention output schema details.

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 concise with three sentences that cover purpose, usage, inputs, outputs, and a reference to related tools. It is front-loaded with the core function and avoids unnecessary words. Slightly more structure (e.g., bullet points) could improve readability, but it remains efficient.

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 the tool's simplicity and the presence of an output schema (context indicates 'Has output schema: true'), the description adequately covers purpose, inputs, outputs, and use case. It mentions the forecast return, which adds value. For a calculator tool, this is reasonably complete, though it could elaborate on error handling or edge cases.

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?

The input schema already covers both parameters (grades and coefficients) with descriptions, achieving 100% schema coverage. The description largely repeats this information ('grades list, optional weights/coefficients') without adding new semantic meaning. It does hint at the forecast output, which indirectly relates to parameters, but baseline 3 is appropriate.

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 clearly states the tool computes simple or weighted grade averages, specifying the verb 'compute' and the resource 'grade average'. It distinguishes from siblings by mentioning 'Use for school report cards' and pointing to list_bundles for related education calculators, making the purpose specific and actionable.

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?

The description provides a clear usage context ('Use for school report cards') and directs users to list_bundles for related calculators, implying when this tool is appropriate. However, it does not explicitly state when not to use it or directly name alternatives, leaving room for improvement.

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