Fuul MCP Server

update_project_tier

Update a project's affiliate tier by modifying name, description, rank, or audience. Validate changes with dry_run before confirming.

Instructions

Updates a project affiliate tier: PATCH /api/v1/projects/:projectId/tiers/:tierId. Optional fields: name, description, rank, audience_id (null clears audience). At least one field required. dry_run then confirmed. Example: {"project_id":"","tier_id":"","rank":2,"dry_run":true}.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project_id": "<project_id>",
      "tier_id": "<tier_id>"
    },
    "name": "update_project_tier"
  }
}

Input Schema

Name	Required	Description
`dry_run`	No	If true, validate and return a preview only; no server mutation.
`confirmed`	No	Must be true to perform the mutation after reviewing dry_run output.
`project_id`	Yes
`tier_id`	Yes
`name`	No
`description`	No
`rank`	No
`audience_id`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.12.0May 30, 2026

TDQS

A3.7/5.0

Behavior4/5

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

With no annotations provided, the description bears full responsibility. It successfully discloses the two-step process (dry_run then confirmed) and the clearing behavior of audience_id. It does not cover authorization needs or error conditions, but the core mutation behavior is well explained.

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 extremely concise: two sentences plus a helpful example. Every sentence earns its place, and the information is front-loaded with the verb and resource.

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?

Given 8 parameters, no output schema, and no annotations, the description covers the essential workflow and parameters. However, it does not describe the return value, error scenarios, or how to construct required fields project_id and tier_id. This leaves some gaps for an AI agent.

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 only 25%, so the description must compensate. It explains that audience_id null clears the audience and that at least one optional field is required. This adds value beyond the schema, but it does not elaborate on other parameters like name or rank beyond their existence. Baseline 3 is appropriate.

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 clearly states the tool updates a project affiliate tier and provides the HTTP method and path. It lists the optional fields and the workflow (dry_run then confirmed). While it does not explicitly differentiate from sibling update tools, the resource and fields are specific enough.

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 usage through the dry_run/confirmed pattern and the requirement of at least one optional field. However, it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions.

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