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inferencia

Auto-created from real demand (207 requests) [x402: 0.01 USDC on Base, pay-per-use]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesentrada

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

D1.6/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose one genuinely useful trait — pay-per-use at 0.01 USDC on Base via x402 — but says nothing about what the operation does, what it returns, latency, or failure modes. Payment cost alone is far short of an adequate behavioral profile for an unannotated tool.

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?

It is short and front-loaded in the trivial sense, but the single sentence spends its length on provenance and pricing rather than the tool's function. Conciseness without a usable purpose statement is under-specification, not clarity.

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?

With no annotations and no output schema, the description is the only source of information, and it omits the tool's core function entirely. An agent has no basis on which to call it correctly beyond guessing from the name.

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?

Single-parameter tool with 100% schema description coverage, so the baseline is 3 even though the description adds nothing. However, the schema's own description ('entrada') is a tautology of the parameter name 'input', so an agent still learns nothing about what content is expected or in what format.

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 never states what the tool does; it only notes provenance (207 requests) and pricing (0.01 USDC on Base). The one-word name 'inferencia' hints at inference, but an agent gets no verb, resource, or capability statement. Sibling tools like 'inference' and 'ai-inference' exist, and nothing here distinguishes this tool from them.

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?

There is no when-to-use guidance, no exclusions, and no reference to any alternative. The agent cannot tell whether this should be called instead of 'inference', 'ai-inference', or 'interpret' for a given task.

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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