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Volume converter

volume_converter

Convert a value between volume units. Units: m³ (Cubic meter), L (Liter), mL (Milliliter), gal_us (US gallon), gal_uk (UK gallon), qt (US quart), pt_us (US pint), pt_uk (UK pint), cup (US cup), fl oz (US fluid ounce). 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?

No annotations are provided, so the description must disclose behavioral traits. It only states that 'Calculation runs on smart-tools.xyz,' which implies an external dependency, but it does not mention return format, error handling, rounding behavior, or the role of the locale parameter (which schema links to 'source_url'). The unit list merely repeats schema enums, so it adds little transparency about actual behavior.

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

Conciseness4/5

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

The description is concise and front-loaded with the core purpose. The unit list is slightly long but necessary for completeness, and each sentence serves a purpose. No redundant filler, though the list could arguably be abbreviated.

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

Completeness3/5

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

For a simple converter, the description covers the main purpose and units, but it omits key contextual details: how the locale parameter affects results (or the 'source_url'), what output format to expect, and any limitations or edge cases. Given no output schema, a bit more context would be helpful, but the tool is simple enough that this is a minor gap.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds full unit names (e.g., 'Cubic meter' for 'm³'), which is modest extra meaning beyond the schema. However, it does not explain the locale parameter's function or the 'source_url' concept, and the value parameter's semantics are already clear from the schema.

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 the tool's function with a specific verb and resource: 'Convert a value between volume units.' It lists all supported units, which also distinguishes it from sibling converters like area_converter or weight_converter. This is a textbook clear purpose statement.

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: this tool is for volume conversions, and the enumerated units make it obvious when to use it. However, it does not explicitly name alternative tools or state when not to use it, but the unit list effectively implies the scope. No exclusions or contraindications are needed for such a straightforward converter.

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.

Resources