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minia2a-mcp

x402-favicon-fetch

Favicon Fetch: Favicon Fetch

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoSize to process
inputNoInput to process
domainNoDomain to process

TDQS

D1.4/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure — and it discloses nothing. It doesn't state that this performs a network request, what the return value looks like, how missing favicons or invalid domains are handled, or whether any side effects occur. The agent is entirely blind to behavior.

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

Conciseness2/5

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

This is under-specification masquerading as brevity, not genuine conciseness. The single phrase wastes its only opportunity by repeating the tool name instead of front-loading any actionable meaning, and there is no structure that separates purpose from usage guidance.

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

Completeness1/5

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

A fetch-oriented tool with 3 parameters, no annotations, and no output schema demands a substantive description, but none exists. The agent cannot determine what input, domain, and size mean, how they interact, or what response to expect — the description is completely inadequate for safe selection and invocation.

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

Parameters3/5

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 even though the tool description itself adds no parameter information. However, the schema's own param descriptions are templated filler ("Size to process", "Input to process", "Domain to process") that don't clarify formats or whether a URL, hostname, or HTML string is expected, so the score stays at baseline rather than rising.

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

Purpose1/5

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

The description "Favicon Fetch: Favicon Fetch" is a pure tautology — it restates the tool name in title-and-body form without adding a single piece of information. There is no verb + resource statement, no mention of what is fetched or how, so an agent can only guess the purpose from the tool name itself.

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

Usage Guidelines1/5

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

The description gives zero guidance on when to use this tool or how it differs from alternatives. With hundreds of siblings like x402-fetch, x402-gravatar, x402-og-image, x402-web-scrape, and x402-url-inspect, the agent has no basis to choose favicon-fetch over any of them.

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.

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