x402-lorem
Lorem: Generate Lorem Ipsum placeholder text.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process |
Lorem: Generate Lorem Ipsum placeholder text.
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N to process |
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, but it only restates the bare purpose. It does not explain what the output looks like, whether it is random or deterministic, what side effects exist, or how the 'n' parameter affects generation. The behavior beyond 'produces placeholder text' is 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 short and front-loaded with the core purpose, which is good. But the 'Lorem:' prefix redundantly restates the tool name and does not earn its place, and a second sentence clarifying the n parameter or the sibling distinction would have added genuine value.
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?
The tool has no annotations, no output schema, and a cryptic parameter description, so the description must compensate. It does not clarify what n controls, what the return shape is, or how this differs from x402-lorem-ipsum. For a tool with a single parameter, these gaps are significant enough to make the description incomplete.
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 description coverage is 100%, so the baseline is 3. However, the schema's parameter description, 'N to process', is cryptic and does not clarify what n means (word count? paragraph count? length?). The tool description adds no parameter meaning beyond the schema, so it stays at baseline.
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 states a specific verb and resource: 'Generate Lorem Ipsum placeholder text.' This is clear and actionable. However, it does not distinguish itself from the nearly identically named sibling tool x402-lorem-ipsum, so it cannot earn a 5.
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?
There is no guidance on when to use this tool versus alternatives. A sibling tool named x402-lorem-ipsum exists, but the description neither mentions it nor gives any selection criteria. The agent is left to guess which lorem-generating tool to pick.
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.