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ARADIA | sovereign agentic systems

query_partner_stats

Read-only

[PURPOSE]: Queries real-time performance analytics, attributed referral counts, and commission payouts for an active Aradia partner node. [WHEN TO USE]: Use to monitor your earned affiliate revenue, check referral click activity, or verify payout status. [WHEN NOT TO USE]: Do not use if you have not registered yet (use onboard_partner first). [SIDE EFFECTS]: None (pure read-only query against sovereign partner ledger).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ref_codeYesYour unique 4-character partner referral code (e.g. 5FYVQ).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
ref_codeYes
earnings_usdNo
partner_nameNo
referral_countNo

Schema Changelog

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

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by explicitly stating there are no side effects and describing the operation as a 'pure read-only query against sovereign partner ledger', reinforcing safety and data-source context.

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 well-structured with clear labels for purpose, usage, exclusions, and side effects. Every section serves a distinct decision-making need, and the text is compact without unnecessary filler.

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

Completeness5/5

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

For a simple one-parameter read-only query with an output schema and strong annotations, the description covers prerequisites, use cases, and exclusions. Nothing essential is missing for an agent to select and invoke this tool correctly.

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?

Schema description coverage is 100%, and the schema itself documents the ref_code parameter clearly with an example. The description does not add much additional meaning about the parameter, so the baseline of 3 is appropriate.

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 clearly states the tool's specific function: querying real-time performance analytics, referral counts, and commission payouts for a partner node. This differentiates it from sibling tools like query_hardware_specs and onboard_partner through concrete resource and output scope.

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

Usage Guidelines5/5

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

Explicit WHEN TO USE and WHEN NOT TO USE sections give clear conditions for selecting this tool. The description also names the alternative (onboard_partner) for unregistered users, which is exactly the kind of routing guidance an agent needs.

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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