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Losbeto — Market Data for AI Agents

account_status

Check whether this connection has an active subscription, how much credit is left and when it expires. Also returns how to subscribe. Call this if a request returned delayed data and you need live.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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. It conveys that this is a read-oriented status check ('Check') and lists returned information, but does not state whether the call has side effects, what happens on failure, or any cost/latency implications. For a simple status check this is adequate but it leaves behavioral nuance unstated given zero annotation coverage.

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?

Two packed sentences cover purpose and return contents, followed by a usage trigger. The purpose is front-loaded and each sentence carries weight. The final trigger sentence adds value but its logic is slightly tangential, so it is concise but not perfectly economical.

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 zero-parameter tool with no output schema, the description covers the essential return values (subscription status, credit, expiry, subscribe instructions) and a usage condition. Minor gaps remain around return format and failure behavior, but the agent has enough to invoke the tool correctly.

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 tool has zero parameters, so per the baseline this scores 4. The empty schema plus 100% (vacuous) coverage means there is nothing for the description to explain — it correctly avoids mentioning parameters that do not exist.

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

Purpose5/5

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

The description states a clear, specific action: check subscription status, credit remaining, and expiry date for this connection. It is clearly distinguishable from the market-data siblings (get_market_data, market_snapshot, etc.) because it addresses account/subscription state rather than market data. The verb 'Check' plus the explicit resource makes the purpose unambiguous.

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

Usage Guidelines4/5

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

Provides an explicit trigger scenario: 'Call this if a request returned delayed data and you need live.' This is a clear when-to-use condition. However, the rationale is somewhat confusing — checking account status to resolve delayed data is not immediately obvious, and no when-not-to-use guidance or alternative tools are named, though siblings are not genuine alternatives here.

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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