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my_referrals

Your referral code and link, agents referred, earnings. You earn 25% of PazAIr commission on every paid order of agents you bring, 12 months each.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It discloses the commission model (25% of PazAIr commission on every paid order, 12 months per agent), which is genuinely useful business context beyond the schema, but says nothing about authentication requirements, pagination, or freshness of the earnings figures.

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 short sentences, front-loaded with what the caller receives before the earnings-model detail. The commission sentence is more context than invocation guidance, but it is brief and not padded.

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 read tool with no output schema and no annotations, the description covers the essentials: what data is returned and the value model behind it. It does not state auth requirements or whether results are paginated, but nothing critical to calling it correctly is missing.

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 takes zero parameters, so there is no parameter semantics to explain; per the rubric a parameterless tool starts at baseline 4. The description's enumeration of returned fields (code, link, agents, earnings) is a bonus, not a requirement.

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 names a specific resource set — your referral code, link, referred agents, and earnings — so an agent knows exactly what this returns. It lacks an explicit verb and doesn't name a sibling it differs from, but the 'my_' scope and referral-domain nouns distinguish it clearly enough from neighbors like share_credit and connect_payouts.

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?

Usage is only implied: an agent can infer it should call this when it needs the current user's referral information. There is no explicit when-to-use statement, no prerequisites, and no mention of alternatives, but for a zero-parameter personal lookup the implied context is sufficient to invoke correctly.

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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