energy_converterConvert a value between energy units. Units: J (Joule), kJ (Kilojoule), cal (Calorie), kcal (Kilocalorie), Wh (Watt-hour), kWh (Kilowatt-hour), BTU (British thermal unit), ft·lb (Foot-pound), eV (Electronvolt). 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions that the calculation runs on smart-tools.xyz, but does not explain output format, precision, locale/source_url behavior, or any side effects. This is minimal transparency for a no-annotation tool.
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 short and front-loaded with the core action and supported units. The only minor issue is the final 'Calculation runs on smart-tools.xyz' sentence, which is vague and adds limited value, but overall it remains concise and scannable.
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?
This is a simple conversion tool with no annotations and no output schema, but the schema fully documents all parameters. The description is sufficient for an agent to understand the tool's domain and available units, though it omits details about the optional locale parameter and expected result format.
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 baseline is 3. The description adds human-readable full names for the enum units (e.g., J = Joule, ft·lb = Foot-pound), which helps an agent understand the unit ids. It does not explain the optional locale/source_url parameter, but the schema already describes it.
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 opens with a specific verb and resource: 'Convert a value between energy units.' It lists the exact unit set, which clearly differentiates this tool from sibling converters like weight_converter or temperature_converter.
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 tool's purpose is immediately clear from the unit list, making it obvious when to use it (energy conversions). It does not explicitly name alternatives or exclusions, but it provides enough context to guide selection among the many converter siblings.
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.