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DataForB2B

DataForB2B MCP Server

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by DataForB2B

Company Enrichment

enrich_company
Read-onlyIdempotent

Get complete company details from public sources: industry, headquarters, employee count, funding, offices, and description.

Instructions

Enrich a single company with full data from public sources (description, industry, headquarters, employee count, funding, offices, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_identifierYesThe company to enrich. Accepts any of: a universal_name slug (e.g. "google"), a LinkedIn company URL (e.g. "https://linkedin.com/company/google"), or an encoded DataForB2B ID (e.g. "org_xxx").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoHTTP-style status code, present only when the call failed.
detailNoError message, present only when the call failed.
companyNoFull company data (description, industry, headquarters, employees, funding, offices, etc.).
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds behavioral context by specifying the data comes from public sources and enumerates fields (description, industry, headquarters, employee count, funding, offices), which helps set expectations about what will be returned. No contradiction with annotations.

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 that clearly states the action and resource, followed by a parenthetical list of examples. Every word adds value and there is zero wasted text.

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

Completeness4/5

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

The tool has one parameter with a fully descriptive schema and an output schema, so the description doesn't need to explain return values. It clearly communicates the single-company scope and the breadth of enrichment data. A slightly more explicit note about alternatives or limitations would make it complete, but it is already strong.

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 coverage is 100%, and the schema already thoroughly describes the company_identifier parameter, including accepted formats. The description does not add additional parameter semantics beyond what the schema provides, matching the baseline for high schema coverage.

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 uses a specific verb ('enrich') with a clear resource ('a single company') and specifies the type of data ('full data from public sources...'). This distinguishes it from siblings like search_company (which likely searches/finds companies) and enrich_profile (which enriches a person).

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 when you have a specific company identifier and need comprehensive enrichment data. However, it does not explicitly compare to alternatives like search_company or state when not to use it. The context 'single company' gives some guidance but no exclusion criteria.

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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