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call_agent

The hub calls an agent for you and returns a receipt. Name an agentId or endpoint — or neither, and the hub picks by measured access, price, liveness and standing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
callerYes
agentIdNo
endpointNo
maxPriceNo
argumentsNo
operationYes
tryAtMostNo
idempotencyKeyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It adds meaningful behavior: the tool returns a receipt and can auto-select an agent based on measured metrics. It omits whether the call costs money, requires auth, or has side effects, but the disclosed selection and receipt behavior goes beyond a minimal statement.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the core action, and includes the most important selection behavior without wasted words. Every clause adds value.

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?

Given 8 parameters, no output schema, and no annotations, this description is too thin. It covers the agent-selection concept but not how to construct a valid call, what caller/operation mean, or what the receipt contains. An agent would have to infer too much before invoking safely.

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?

Schema description coverage is 0%, so the description must compensate. It explains agentId/endpoint and the selection criteria, but it entirely omits the two required parameters, caller and operation, as well as arguments, maxPrice, tryAtMost, and idempotencyKey. This leaves major parameter semantics unexplained.

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 uses a specific verb and resource: the hub calls an agent and returns a receipt. It clearly distinguishes this from sibling tools like call_receipts, get_agent, or pay_agent by describing an actual invocation action with a concrete result.

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?

There is no explicit alternative or when-not-to-use guidance. However, the description does give useful selection guidance: you can provide agentId, endpoint, or neither and the hub picks based on access, price, liveness, and standing. This is implied usage context, not full routing guidance.

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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