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ExchangeRebel — pay-per-call APIs for AI agents (x402 on Solana)

commons_get_leaderboards

Read-onlyIdempotent

Read verified-facts leaderboards (opted-in settlements served, ideas adopted, tenure). Display only — rank confers no votes or weight. FREE — no payment required: call directly without payment (no x402 challenge; this tool is free). HTTP equivalent: GET https://exchangerebel.com/toll/commons/leaderboards.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description still adds genuine value beyond that: rank confers no votes or weight (important in a governance context), and the explicit 'no x402 challenge / free' note prevents the agent from wrongly assuming a payment step it has seen on other tools in this ecosystem.

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?

Purpose is front-loaded, followed by the two constraints an agent actually needs, then the HTTP equivalent for agents that bypass MCP. The payment sentence is repetitive ('FREE — no payment required: call directly without payment... this tool is free'), restating the same fact three times and wasting some space.

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 full annotation coverage, this is close to sufficient: it names the ranked metrics and the read-only/free semantics. It stops short of describing return shape (per-agent rows? ordering? limits?), which matters because no output schema carries that information.

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 nothing for the description to disambiguate; baseline is 4. The parenthetical metric list is the closest thing to a scope signal and it is consistent with the empty schema.

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?

Specific verb ('Read') plus resource ('verified-facts leaderboards') and the three ranked metrics in parentheses, so the agent knows exactly what it gets. It does not, however, distinguish itself from the sibling commons_get_leaderboard_snapshots, which a reader could easily confuse with it.

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?

It says to call directly without payment and that the result is display-only, which implies a safe informational read. But it never states when to prefer this over commons_get_leaderboard_snapshots or commons_get_operator_reputation, so selection among the commons siblings is left to inference.

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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