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kuyen-labs

Fuul MCP Server

by kuyen-labs

approve_payouts

Use dry run to preview payout approvals, then confirm to execute. Filter payouts by IDs or date range for targeted approval.

Instructions

Approves payouts: PATCH /api/v1/projects/:projectId/payouts/approve. Body: payout_ids OR date filters (server validates mutual exclusivity). dry_run then confirmed. Example dry_run: {"project_id":"","payout_ids":[""],"dry_run":true}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNoIf true, validate and return a preview only; no server mutation.
confirmedNoMust be true to perform the mutation after reviewing dry_run output.
project_idYes
payout_idsNoMutually exclusive with from_date/to_date filters on server.
from_dateNo
to_dateNo
user_addressNo
affiliate_addressNo
Behavior2/5

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

No annotations are provided, so the description must disclose all behavioral traits. It mentions the endpoint and parameter constraints (mutual exclusivity, two-step flow) but does not describe error handling, side effects, rate limits, or what happens when confirmed is false. The description is insufficient for full transparency.

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 a single sentence that immediately states the purpose, then provides the endpoint, parameter constraints, and an example. It is front-loaded and efficient, with no extraneous information. Every part adds value.

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

Completeness3/5

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

With 8 parameters and no output schema, the description covers the core logic (mutual exclusivity, two-step) and includes an example. However, it lacks details on return values, error scenarios, and the exact behavior of the confirmed parameter. Completeness is adequate but not thorough.

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?

Schema description coverage is low (38%), so the description must add meaning. It clarifies that payout_ids and from_date/to_date are mutually exclusive on the server, and that dry_run must be done before confirmed. It also provides an example JSON. However, it omits user_address and affiliate_address parameters.

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?

Description clearly states 'Approves payouts' and includes the HTTP endpoint PATCH /api/v1/projects/:projectId/payouts/approve. It specifies the key parameters (payout_ids or date filters) and the two-step process (dry_run then confirmed). This distinguishes it from sibling tools like reject_payouts and list_payouts_pending_approval.

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?

The description implies a sequential process: run dry_run first, then confirmed. However, it does not explicitly state when to use this tool over alternatives (e.g., reject_payouts) or provide prerequisites or authorization hints. Usage context is somewhat clear but lacks thorough 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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