calculate_gpa
Gpa calculator
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| scale | No | ||
| courses | Yes |
Gpa calculator
| Name | Required | Description | Default |
|---|---|---|---|
| scale | No | ||
| courses | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral context whatsoever (no mention of scale handling, grade interpretation, or output form), leaving the annotation-derived baseline untouched.
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?
Two words are trivially concise, but here brevity is under-specification rather than efficiency. There is no front-loaded purpose or any content that earns its place because there is essentially no content.
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 a nested array parameter, a required field, an enum scale, and no output schema, the description is completely inadequate. An agent cannot determine units, expected grades format, or the effect of the scale parameter without guessing.
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 two parameters exist, so the description bears full responsibility for explaining them. It says nothing about `courses` (array of grade/credit objects) or the `scale` enum ("4.0" vs "percent"), missing the most consequential detail for correct invocation.
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?
"Gpa calculator" restates the tool name with a vague noun phrase and no specific verb or scope. It distinguishes nothing from the ~50 sibling calculators (calculate_bmi, calculate_bmr, etc.), all of which follow the same naming pattern.
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 guidance on when to use this tool, what inputs it expects, or how it differs from neighboring calculators. Any agent must infer everything from the schema alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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