unit_price_calculatorCompare price per unit of two packs and report which is cheaper. Runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | Language for the source_url link (default en) | |
| price_a | Yes | Price of pack A | |
| price_b | Yes | Price of pack B | |
| quantity_a | Yes | Quantity in pack A | |
| quantity_b | Yes | Quantity in pack B |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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, but it only states the basic operation. It does not mention what the tool returns (e.g., a source_url link), how it handles edge cases like equal unit prices, or any side effects. The phrase 'Runs on smart-tools.xyz' hints at remote execution but is vague.
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 and front-loaded, with the core function stated in the first sentence. The second sentence ('Runs on smart-tools.xyz') adds marginal value but does not clutter the message. It is appropriately sized for a simple 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?
The tool has no output schema, so the description should explain the return value, but it only says 'report which is cheaper' without details. The locale parameter's description in the schema reveals that a source_url link is part of the output, which the tool description does not mention. Edge cases (e.g., equal prices) are also unaddressed.
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 has 100% coverage with descriptions for all five parameters, so the baseline is 3. The tool description adds no additional meaning beyond the schema, leaving the parameter semantics entirely to the schema's field descriptions.
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's function: comparing price per unit of two packs and reporting which is cheaper. This specific verb phrase and resource ('two packs') distinguishes it from sibling calculators like discount_calculator or percentage_calculator, making the purpose unmistakable.
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 implies usage when comparing unit prices of two packs, but it does not explicitly state when to use this tool over alternatives or provide exclusions. There is no mention of when not to use it (e.g., for more than two packs), but the context is clear from the purpose.
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.