x402-is-rgba
Is Rgba: Validate an RGBA color string like rgba(255,0,0,0.5) with channels 0-255 and alpha 0-1. Provide value.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Is Rgba: Validate an RGBA color string like rgba(255,0,0,0.5) with channels 0-255 and alpha 0-1. Provide value.
| 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 behavioral burden. It usefully discloses the accepted ranges and example format. However, it does not say what the tool returns or how it behaves on invalid input, so the result contract is left unspecified.
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 compact and front-loaded: it names the operation and the acceptance criteria in two sentences. The only minor waste is the redundant 'Is Rgba:' prefix and the terse 'Provide value' phrase.
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 low-complexity validation tool, but with no annotations and no output schema the description should cover both input and output. It covers the accepted input format but omits what the function returns, and the empty schema makes the invocation mechanics unclear.
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 zero properties, and the description adds value by defining the expected string shape and the range rules. But the instruction 'Provide value' is ambiguous: there is no parameter name or argument slot in the schema, so an agent is left unsure how to pass the input to this tool.
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 ('Validate') and a specific resource (an RGBA color string), gives a concrete example format ('rgba(255,0,0,0.5)'), and states the validity ranges (channels 0-255, alpha 0-1). It does not explicitly compare against siblings like x402-is-rgb, but the scope is clear enough to tell this validator apart from them.
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 described format and ranges imply when this tool is appropriate: validating an RGBA string. However, there is no explicit guidance about when to use it instead of a sibling such as x402-is-rgb or x402-is-hex-color, and no mention of alternatives or exclusions.
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.