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x402-payments-landscape

INDUSTRY REPORT: Landscape de pagos x402 (deep, cited). input=optional scope. B2B: fundadores/inversores entienden el ecosistema de micropagos para IA. [x402: 75.0 USDC on Base, pay-per-use]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesservice input

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does indicate that the report is 'deep, cited' and that input is 'optional scope,' which gives some behavioral context. However, it does not describe output format, citation style, or any limitations, leaving the agent to infer much of the tool's behavior.

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

Conciseness4/5

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

The description is compact and front-loaded with the core purpose ('INDUSTRY REPORT'), then adds audience and parameter context. It includes an example that helps disambiguate scope. The all-caps formatting and fragment structure are somewhat noisy but do not waste words.

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

Completeness4/5

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

For a single-parameter report generator with no output schema, the description is reasonably complete: it names the deliverable, the topic, the intended audience, and clarifies that the only input is an optional scope. It still leaves some uncertainty around output structure, but that is less critical for this simple tool shape.

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

Parameters4/5

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

The input schema only describes the parameter as 'service input,' which is generic and unhelpful. The description adds meaningful semantics by stating 'input=optional scope' and providing a concrete example ('x402: 75.0 USDC on Base, pay-per-use'), clarifying what an agent should pass and that the field is optional.

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 clearly identifies the tool as an 'INDUSTRY REPORT' on the 'Landscape de pagos x402,' distinguishing it by its specific subject matter. It goes beyond a tautology by noting the depth ('deep, cited') and target audience (B2B founders/investors). However, it does not explicitly differentiate itself from sibling reporting tools like crypto-payments-2026 or latam-fintech-report, other than by topic.

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

Usage Guidelines3/5

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

The intended use is implied through the audience specification ('fundadores/inversores') and the focus on understanding the micropayment ecosystem for AI. It provides a clear context but does not state when not to use this tool or explicitly mention alternatives among the many report/research siblings.

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

C2.6/5.0
Disambiguation1/5

The set contains many trivially indistinct tools: ai-inference/inference, compress/comprimir, count-tokens/contar-tokens, detect-language/language-detect, and multiple overlapping OCR receipt variants. With 160 tools and pairs that differ only by language or suffix, an agent cannot reliably distinguish several capabilities.

Naming Consistency3/5

Most names are readable lower-hyphen identifiers, but they mix action verbs, noun phrases, domain prefixes, pipeline suffixes, Spanish/English, and arbitrary demo/batch labels. There is a loose convention, but no consistent verb_noun pattern.

Tool Count1/5

160 tools on one server is an extreme count and clearly unwieldy. Even as a marketplace, exposing every variant, demo, and composed bundle as a top-level MCP tool overwhelms agent selection and adds little distinct capability.

Completeness3/5

The set covers a huge range of text, image, audio, code, market, compliance, and content-workflow tasks, so many intents have some available tool. However, it is a grab-bag rather than a defined service surface, and the arbitrary demo/specialized variants make it unclear whether a needed operation truly exists or is just a duplicate.

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