x402-soundex
Soundex: Encode a name into a Soundex code (letter + 3 digits) for fuzzy name matching. Provide name or word.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Name to process | |
| word | No | Word to process |
Soundex: Encode a name into a Soundex code (letter + 3 digits) for fuzzy name matching. Provide name or word.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Name to process | |
| word | No | Word to process |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral disclosure. It discloses that the tool transforms a name/word into a normalized Soundex code and specifies the return format (letter + 3 digits), which is useful. However, it does not disclose behavior for edge cases such as invalid characters, empty input, or what happens if both name and word are provided. This is a meaningful gap for a tool with no annotation safety net.
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, well-organized sentence that front-loads the algorithm and output format, then states the purpose and input instruction. Every clause adds necessary information and there is no wasted text.
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?
For a simple transformation tool with no output schema, the description provides the essential return shape (letter + 3 digits) and input expectation. It does not cover edge-case behavior, but the tool is low complexity and the core contract is clear. A brief note on invalid or non-alphabetic input would make it fully complete.
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% since both parameters have descriptions, so the baseline is 3. The description adds value by clarifying that you can provide 'name or word', implying they are interchangeable and that only one is needed. This goes slightly beyond the schema's generic 'Name to process' / 'Word to process' labels, though it does not explain precedence if both are supplied.
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 specific verb and resource: encode a name into a Soundex code, including the exact output shape (letter + 3 digits). It also gives the purpose (fuzzy name matching), so an agent can tell what it does. However, it does not explicitly distinguish itself from the phonetically similar sibling x402-metaphone, so it falls short of full sibling differentiation.
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 provides clear usage context: use it for fuzzy name matching and provide a name or word. It directly instructs the agent on what input to supply. It does not mention exclusions or alternatives like x402-metaphone, so it earns a 4 rather than a 5.
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.
The tool set is saturated with near-duplicates and synonyms: character-count vs char-count, clamp vs clamp-value, is-abundant vs is-abundant-num vs is-abundant-number, and fetch vs browser-scrape vs web-scrape vs text-scrape. Generic names like 'difference', 'normalize', 'range', and 'partition' make the boundaries even harder for an agent to determine.
Most tools share a x402- kebab-case prefix, but the set mixes noun-only names (math, hash, prime, time), verb-first names (get_stats, find, validate), auto-generated names (x402-publish-1787853294312-base-account), and inconsistent variants like temp vs temperature vs temperature-convert. This is not a coherent verb_noun convention despite the common prefix.
1677 tools is an extreme count that creates selection paralysis and makes coherent agent use impractical. A utility or marketplace server at this scale needs sub-services or namespacing rather than a flat tool list.
The surface has broad token coverage across many utility categories, but the marketplace aspect is incomplete: service_discovery and get_stats exist, yet there are no generic publish, update, delete, or account-management operations. Utility families also contain redundant variants without clear completion or lifecycle structure.