B2Brilliant MCP Server

refine_user_business

Refine business data by applying user feedback to fix errors, fill gaps, and improve accuracy for better analysis and outreach.

Instructions

Refine your business information based on feedback

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": {
      "business": "<business>",
      "feedback": "<feedback>"
    },
    "name": "refine_user_business"
  }
}

Input Schema

Name	Required	Description	Default
`business`	Yes	Business object from discover_user_business
`feedback`	Yes	Feedback to improve the business information

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 9, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It does not reveal what refining entails, whether it modifies the existing business object, what the output looks like, or any side effects. The terse wording lacks critical behavioral 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 a single, front-loaded sentence with no filler or redundancy. It efficiently communicates the core purpose, though at the cost of depth, which is the appropriate trade-off for this terse format.

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

Completeness2/5

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

For a tool with two parameters and no output schema, the description does not explain the refinement process, return value, or dependencies on discover_user_business. The context is too sparse for an agent to predict the tool's behavior or integrate it effectively alongside sibling tools.

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?

The input schema already provides full descriptions for both parameters (business object from discover_user_business, feedback string). The description adds only the phrase 'based on feedback', which mirrors the schema, so no meaningful additional semantic value is provided beyond the structured fields.

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 states a specific action ('refine') on a specific resource ('your business information') motivated by 'feedback'. It distinguishes from sibling 'refine_business' by adding the qualifier 'your' and the feedback trigger, though it doesn't explicitly contrast with the generic sibling.

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 phrase 'based on feedback' implies usage after receiving feedback, but the description gives no explicit guidance on when to use this versus the sibling 'refine_business' or 'discover_user_business'. No exclusions or alternatives are mentioned.

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

Deploy Server