Fuul MCP Server

list_payout_schemas

List payout schema metadata including reward types and create payload examples to prepare for creating incentives.

Instructions

Lists payout schema metadata from GET /public-api/v1/metadata/payout-schemas (cached), enriched for create_incentive. Includes enums, payout_term_dto.schemes (per PayoutScheme), plus reward_types[] with create_payload_example for: fixed-reward, variable-reward, proportional-pool, leaderboard. Top-level create_incentive_payload_guide documents body shape and webapp encode.ts mappers. Call before create_incentive. Params: {}.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_payout_schemas"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.12.0May 30, 2026

TDQS

A4.4/5.0

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses caching, output structure (enums, reward_types, create_payload_example), and links to webapp mappers. While it doesn't explicitly state read-only or side-effect-free, the listing nature and GET path imply it. The detail compensates for missing annotations.

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?

Description is dense but well-structured: front-loads purpose, then lists output details. Every sentence adds value. Could be slightly more structured with bullet points, but overall efficient and readable.

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?

Given zero parameters and no output schema, the description provides extensive context: cached data, enums, reward types with examples, and a top-level payload guide. It fully prepares the agent for what to expect and how to use the output with create_incentive.

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?

Tool has zero parameters; schema coverage is 100%. Baseline for 0 params is 4. The description adds substantial value by detailing the output structure, going beyond schema requirements. It compensates for the lack of parameters by explaining what the tool returns in depth.

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 lists payout schema metadata from a specific API endpoint, enriches it for create_incentive, and enumerates detailed contents. It distinguishes itself from siblings like list_incentives and list_chains by specifying its purpose and linkage to create_incentive.

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?

Explicitly states 'Call before create_incentive,' providing a clear when-to-use directive. It does not enumerate when not to use or alternatives, but the context and explanation of enrichment for create_incentive imply its specific role. The caching mention hints at staleness considerations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.