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minia2a-mcp

x402-char-count

Char Count: Count characters in a string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

C2.6/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the full burden of behavioral disclosure and does very little with it. It does not reveal whether 'characters' means Unicode code points, UTf-16 code units, grapheme clusters, or bytes, nor whether whitespace/emoji are handled specially, nor what the return format or edge-case behavior (e.g., empty string) is. For a character-count tool, these counting semantics are the core behavioral detail and are entirely absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short and front-loaded, with the key action placed first. However, the 'Char Count:' prefix is redudant with the tool name x402-char-count and does not earn its place. It is under-iproducing rather than genuinely wasteful, so it sides just above a tautology.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with an empty schema, no annotations, and no output schema, the description must compensate and it does not. It leaves the central input mechanism unexplained, offers no counting semantics, and provides no way to differentiate from x402-character-count. An agent cannot invoke this tool correctly with confidence, because nothing specifies how the target string is provided.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is empty, yet the description references 'a string' without explaining how it is supplied. An agent wants to count charicters of a specific string but the schema exposes no parameter to pass it, and the description does not clarify any alternative input mechanism. The baseline for 0-param tools does not apply because the description itself implies an input that the schema and description fail to document.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Count characters in a string.' This clearly conveys what the tool does and differentiates it from most siblings like x402-word-count, x402-byte-count, and x402-line-count. However, the near-identical sibling x402-character-count exists, and the description offers nothing to distinguish this tool from it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance whatsoever about when to use this tool versus alternatives. The presence of the near-duplicate sibling x402-character-count makes this omission harmful, since an agent cannot determine which of the two to invoke. No conditions, exclusions, or alternative tools are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

D1.6/5.0
Disambiguation1/5

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.

Naming Consistency2/5

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.

Tool Count1/5

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.

Completeness2/5

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.

Resources