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Glama

Area converter

area_converter

Convert a value between area units. Units: km² (Square kilometer), m² (Square meter), cm² (Square centimeter), mm² (Square millimeter), ha (Hectare), ac (Acre), mi² (Square mile), ft² (Square foot), yd² (Square yard), in² (Square inch). Calculation runs on smart-tools.xyz.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYesTarget unit id
fromYesSource unit id
valueYesAmount to convert
localeNoLanguage for source_url (en, de, es, fr, it, nl, uk)

TDQS

A3.6/5.0
Behavior2/5

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It mentions 'Calculation runs on smart-tools.xyz' but does not clarify whether the operation is read-only, whether data is stored, what the response format is, or any error handling. For a conversion tool, this is a significant transparency gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long and front-loaded with the main action, followed by a tidy list of units. Every sentence earns its place; there is no redundant or filler text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description fails to state what the tool returns or how the result is structured. It also lacks detail on precision, rounding, or behavior for invalid inputs. For a tool that an agent must invoke and interpret, this is incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers all four parameters with descriptions and enum constraints, so baseline is 3. The description adds full names for the unit abbreviations (e.g., 'Square kilometer'), but it does not explain the 'locale' parameter or provide additional semantic details. Schema already does the heavy lifting, so no higher score is warranted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Convert a value between area units' with a specific verb and resource, and it enumerates the exact units supported. This distinguishes it from sibling converters (length, temperature, etc.) and leaves no ambiguity about its function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context by listing all supported area units, making it obvious when to use this tool versus other converters. It does not explicitly state when not to use it, but the unit scope implicitly serves as usage guidance.

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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TDQS

B3.3/5.0
Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness4/5

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.

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