gpa_calculatorWeighted grade point average from letter grades (US 4.0 scale, +/-) or numeric grade points and credit hours. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | Language for the source_url link (default en) | |
| courses | Yes | Each course as { grade, credits }. grade is a letter (A, A-, B+ …) or numeric grade points (0–4.5); credits defaults to 1. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains the core computation and accepted input types, but omits details such as how invalid grades are handled, rounding behavior, or the response format. This is adequate but not rich.
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 a single sentence and front-loaded with the core purpose. The trailing 'Runs on smart-tools.xyz' is extraneous and does not serve the agent, slightly reducing conciseness.
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?
The tool has two parameters (one nested array), no annotations, and no output schema. The description explains inputs and scale but does not state what the tool returns (e.g., a numeric GPA, JSON, or display format). For a simple calculator, this is a notable gap but not fatal.
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 100%, so the description need not repeat parameter details. It does add context about the US 4.0 scale and plus/minus, which aligns with the 'grade' parameter, but it does not go beyond the schema's descriptions. Baseline score of 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 a 'weighted grade point average' from letter grades or numeric grade points with credit hours. It specifies the US 4.0 scale and +/- grading, which distinguishes it from other calculator tools in the sibling list.
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 does not mention when to use this tool instead of alternatives, nor any exclusions or prerequisites. The phrase 'Runs on smart-tools.xyz' is irrelevant for usage guidance. There is no explicit context like 'Use for academic GPA calculations'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinct, but there are notable overlaps. 'hash_generator' and 'file_hash' effectively do the same thing (SHA hashing of text), and several CSV/TSV converters (csv_to_json, csv_to_sql, table_to_csv, markdown_table) have similar input handling, though outputs differ. The sheer number of converters is clear, but these near-duplicates create some ambiguity.
Names follow a generally consistent pattern: lowercase with underscores, often ending in 'converter', 'calculator', or 'generator'. A few names like 'base64', 'lorem_ipsum', and 'transliteration' deviate from the suffix pattern, but the naming style is uniform and predictable overall.
With 73 tools, this server is far over the typical well-scoped range. While the broad utility-toolkit purpose might justify a larger set, 73 is unwieldy and pushes well into 'too many' territory, making it harder for an agent to select the right tool efficiently.
The server covers a remarkably wide range of common utilities: unit conversions, calculators, text transformations, development helpers (JSON, regex, JWT, subnet), and generators. Minor gaps exist (e.g., currency converter, time zone converter), but for a general-purpose toolkit, it is largely comprehensive.