Versium REACH

C2B Append Mcp Tool

c2b_append

Read-onlyIdempotent

Get business demographic details for consumers. Identify the consumer with a LinkedIn URL, or with first name, last name, and one of: email, phone, or city and state. Retrieve job title, seniority, department, business email, LinkedIn profile, and complete business information.
Use this tool when users ask for 'C2B', 'c2b', or 'Consumer to Business Person' data

**Tips for Best Results:**
- Provide full name and consumer email for best match quality
- LinkedIn URLs must be in format: linkedin.com/in/username
- Use `rcfg_require_email` to return only records with business email
- Use `rcfg_require_value` to filter by job title, department, or other attributes

Input Schema

TableJSON Schema

Name	Required	Description
`city`	No	A person's city
`last`	No	A person's last name
`email`	No	A valid consumer email address
`first`	No	A person's first name
`phone`	No	A person's phone number
`state`	No	A person's two-letter state code
`domain`	No	A business domain
`li_url`	No	A LinkedIn URL (accepts https://www.linkedin.com/in/username, www.linkedin.com/in/username, or linkedin.com/in/username)
`rcfg_max_time`	No	Maximum allowed API run time (in seconds)
`rcfg_require_email`	No	Returns only records with email (set to 1 to enable)
`rcfg_require_value`	No	Field/value requirements in "Field=Value" format. Example: ["Title=Manager"]

Output Schema

TableJSON Schema

Name	Required	Description
`results`	No	Records returned by the Operations API. Record fields pass through unchanged.
`query_id`	No
`warnings`	No
`input_query`	No
`num_matches`	No	Number of matching queries.
`num_results`	No	Number of records returned.
`match_counts`	No	Sparse match counts. An absent key means zero.

TDQS

A4.8/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false, idempotentHint=true, destructiveHint=false, covering the core behavioral traits. The description adds context about the matching logic (anyOf combinations) and configuration parameters (rcfg_*), but doesn't introduce conflicting or additional behavioral traits. It's consistent and slightly enriches understanding without redundancy.

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 concise yet comprehensive. It opens with a clear purpose, includes a usage trigger, and breaks out tips in a bulleted list. Every sentence adds value; no fluff or repetition of schema details. Front-loaded with the core function, making it easy to scan.

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

Completeness5/5

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

Given the complexity (11 params, anyOf constraints) and that an output schema exists, the description adequately covers the essential context: required input combinations, configuration options, and best practices. It does not need to explain return values (output schema handles that), and it provides enough guidance for an agent to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage with each parameter described, but the description adds extra meaning by explaining the anyOf grouping (which parameter sets are valid), the intended use of rcfg_require_email and rcfg_require_value, and the LinkedIn URL formats. This goes beyond the schema to clarify business logic and configuration semantics.

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?

The description clearly states the tool's purpose: 'Get business demographic details for consumers' and specifies the identification criteria (LinkedIn URL or name+email/phone/city-state). It also lists the output fields (job title, seniority, department, business email, LinkedIn profile, complete business information), making it specific and distinguishable from sibling tools via the explicit 'Use this tool when users ask for C2B' guidance.

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

Usage Guidelines5/5

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

The description provides explicit usage cues: 'Use this tool when users ask for C2B, c2b, or Consumer to Business Person data'. It also gives best-practice tips (provide full name and email, LinkedIn URL format, use rcfg_require_email and rcfg_require_value for filtering), guiding when and how to use the tool effectively without ambiguity.

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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TDQS

A4.1/5.0

Disambiguation5/5

Each tool targets a distinct resource and action: list generation (B2B vs B2C), enrichment (contact, demographic, firmographic, C2B, IP-to-domain), project/list management, job lifecycle, and validation. No two tools appear to do the same thing, so an agent can reliably select the correct one.

Naming Consistency5/5

All tool names follow the verb_noun pattern consistently, using verbs like list, show, create, preview, search, validate, append, and estimate. Even the segmented append tools (c2b_append, contact_append, demographic_append, firmographic_append, ip_to_domain_append) follow the same pattern with clear noun modifiers. No mixed conventions or vague verbs.

Tool Count4/5

With 19 tools, this is on the higher side but still well-scoped for a data enrichment and list-building platform. The count covers distinct functional areas (audience estimation, enrichment, job/project management, list inspection, documentation) without unnecessary bloat. It feels slightly heavy but each tool earns its place.

Completeness4/5

The tool surface covers the core workflows: estimating audiences, creating and monitoring jobs, managing projects and lists, and enriching records with various data types. Minor gaps exist, such as no explicit delete/update operations for projects or lists, and no direct file download for list contents (though preview_list and show_list provide partial coverage). These are non-blocking gaps that agents can work around.

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