length_converterConvert a value between length units. Units: km (Kilometer), m (Meter), cm (Centimeter), mm (Millimeter), µm (Micrometer), mi (Mile), yd (Yard), ft (Foot), in (Inch), nmi (Nautical mile). Calculation runs on smart-tools.xyz.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target unit id | |
| from | Yes | Source unit id | |
| value | Yes | Amount to convert | |
| locale | No | Language for source_url (en, de, es, fr, it, nl, uk) |
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. It mentions 'Calculation runs on smart-tools.xyz' but this is not a behavioral trait (it does not clarify return format, error handling, rounding, or side effects). No information about edge cases, locale effects, or the meaning of 'source_url' appears, leaving significant behavioral aspects undisclosed.
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, with the key purpose stated upfront. The unit list is necessary and compact. However, the closing sentence 'Calculation runs on smart-tools.xyz' adds little functional value and reads as clutter, preventing a perfect score.
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?
Given the tool's simplicity, the description covers basic conversion purpose and unit list, but it omits important contextual details: no mention of what the response includes (e.g., a converted value or a source URL), how the 'locale' parameter affects output, or any behavioral caveats. With no output schema and no annotations, the description is incomplete for a fully informed agent.
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?
While schema description coverage is 100%, the schema only labels 'from' and 'to' as 'Source unit id' and 'Target unit id' without explaining the unit codes. The description expands these codes to full names ('km (Kilometer)', etc.), adding meaning beyond the schema. However, it does not explain the 'locale' parameter or its relationship to 'source_url', which is a gap given the schema's brief description.
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 with a specific verb and resource: 'Convert a value between length units.' It explicitly lists all supported units, distinguishing it from sibling converters (e.g., area, temperature, weight). The name and title are reinforced without tautology.
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 context ('Convert a value between length units') but does not provide explicit guidance on when to use this tool vs. alternatives. No mention of when not to use or pointers to sibling converters for non-length units. The distinction is implied by the unit list, but no direct exclusions or alternatives are stated.
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.