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LiquidBuiltIt

B2Brilliant MCP Server

refine_business

Refine business information by applying feedback to fix inaccuracies and improve relevance for outreach campaigns.

Instructions

Refine target business information based on feedback

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
businessYesBusiness object from discover_business
feedbackYesFeedback to improve the business information
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'refine', which implies a mutation, but gives no details about side effects, idempotency, whether the original business object is modified, or what the response will be. This is a significant gap for a write operation.

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, concise sentence with no redundant words. It effectively communicates the tool's action without over-explaining, earning the highest score for efficiency.

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?

Given the tool's mutation nature, no output schema, and no annotations, the description is incomplete. It does not explain the workflow context (e.g., after discover_business), what 'refine' means in terms of output, or how the feedback is applied. The minimal information leaves the agent to infer too much.

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 schema documents both parameters with descriptions, and the parameter descriptions add context beyond the schema: 'business' references discover_business, establishing a clear data source, and 'feedback' explains its purpose. This cross-tool reference is useful, though it does not detail the expected structure of the business object or feedback format.

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 uses the specific verb 'refine' on 'target business information' with feedback as the input, clearly stating what the tool does. However, it does not distinguish itself from the sibling tool 'refine_user_business', which likely has a very similar purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like refine_user_business or discover_business. The description implies a workflow of refining an existing business object with feedback, but does not state prerequisites, exclusions, or fallback tools.

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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