x402-format-integer
Format Integer: Format an integer.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Format Integer: Format an integer.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it discloses nothing: it does not explain what 'format' means, how the tool receives its input (the schema has zero parameters), whether it is a pure read operation, or how it behaves on edge cases.
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 extremely short but this is under-specification rather than true conciseness: the lead-in 'Format Integer:' and the sentence 'Format an integer.' are redundant with the tool name and carry zero informative 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?
For a zero-parameter tool with no annotations and no output schema, an agent needs the description to clarify invocation and expected output. Instead it receives only a tautology, which is completely inadequate given the tool's ambiguous siblings and unexplained empty input schema.
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 schema has zero properties, so there are no parameters for the description to document; the rubric's 0-parameter baseline of 4 applies. The description does fail to explain where the integer input comes from, but that gap is more about behavioral transparency than parameter semantics.
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?
"Format Integer: Format an integer." restates the tool name without adding specific meaning. It names a verb and resource but fails to specify what formatting operation is performed, and it does not distinguish itself from dozens of formatting siblings such as x402-format-thousands, x402-format-decimal, x402-format-fixed, or x402-to-fixed.
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?
No guidance is provided on when to choose this tool over its many formatting and number-related siblings (x402-format-fixed, x402-format-scientific, x402-number-humanize, x402-zero-pad, etc.). The vague wording 'Format an integer' gives an agent no decision criteria for selection.
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.