Convert a value between units of the same category: length, mass, volume, speed, area, digital storage, time, and temperature (Celsius/Fahrenheit/Kelvin).
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | Target unit in the SAME category as 'from', e.g. 'mi', 'km', 'lb', 'F'. | |
| from | Yes | Source unit, e.g. 'km', 'mi', 'kg', 'lb', 'C', 'F', 'GB', 'm/s'. | |
| value | Yes | The numeric value to convert. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the basic function without revealing behaviors such as handling of invalid units, precision, error messages, or whether it is read-only (though conversion is inherently non-destructive). The description lacks depth expected for a tool with no annotations.
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 a single sentence that is front-loaded with the action and includes a list of categories. Every word serves a purpose; no redundancy or filler.
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 (3 parameters, no output schema, no annotations), the description adequately covers the supported categories but lacks details on error handling, output format, or examples. It is sufficient for basic usage but not fully comprehensive.
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% description coverage, so the baseline is 3. The description lists categories but does not add meaningful extra information beyond what the schema already provides (e.g., 'from' and 'to' unit examples are in the schema). It does not explain parameter syntax or constraints beyond the schema.
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 purpose: converting a value between units within the same category. It enumerates specific categories (length, mass, volume, etc.), distinguishing it from sibling tools like convert_currency or convert_timezone. The verb 'convert' and resource 'units of the same category' are precise.
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 that the tool is for unit conversions within a category and hints at required parameters (value, from, to) being in the same category. It does not explicitly state when not to use it or provide alternatives, but the sibling tools cover other conversion types, providing implicit differentiation.
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 target clearly distinct operations, and the descriptions carefully disambiguate the large timezone cluster (convert_timezone, convert_batch, now_in, tz_offset, list_timezones, lookup_timezone). The main sources of possible confusion are similar name stems like extract vs extract_entities and convert_timezone vs convert_batch, but their stated purposes are distinct enough.
There is a mix of conventions: many verb_noun names (convert_timezone, memory_search, list_timezones), bare verbs (chat, extract, summarize, price), noun-only names (status, qr_code), and odd forms like now_in and tz_offset. The set is readable but not predictable enough for a clear single naming pattern.
With 26 tools, the server exceeds the 25+ threshold for 'too many' and spans at least seven unrelated domains: AI text, time, currency, memory, web extraction, URLs, and webhooks. Each tool may earn its place individually, but the overall tool surface is broad and heavy for an agent to scan efficiently.
Timezone and text-processing workflows are well covered, but some subdomains have notable gaps: memory has upsert/search but no delete, currency only supports conversion without currency listing, and short-link/webhook areas lack management operations. The request_feature tool can surface missing capabilities, but it does not fill the gaps itself.