Versium REACH

Preview List Mcp Tool

preview_list

Read-onlyIdempotent

Preview a sample of rows from a REACH list.

Use this tool to inspect the actual data rows in a list. Returns a row sample
from the list file. The optional `count` parameter is a hint for how many rows
to return; the actual number may differ depending on list type and backend
preview behavior. When omitted, the service default applies.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`count`	No	Hint for number of rows to return (1–25). Actual rows may vary by list type. When omitted the service default is used.
`list_id`	Yes	Positive integer list ID (must be ≥ 1)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`rows`	No
`list_id`	No
`list_url`	No
`returned_rows`	No

TDQS

A4.1/5.0

Behavior4/5

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral nuance beyond the annotations, including that the count parameter is only a hint, the actual row count may differ by list type and backend behavior, and a service default applies when omitted. This is helpful and consistent with the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the primary purpose. It covers sample behavior, count variability, and default behavior in four short sentences. There is slight redundancy between 'Preview a sample of rows' and 'Returns a row sample', but no substantial waste.

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?

For a simple two-parameter read-only preview tool with full schema coverage and an output schema, the description context is appropriately complete. It explains the extent of the sample, the count limitations, and backend variability. It does not address all possible sibling distinctions, but that is not essential for using this tool correctly.

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 schema already has 100% coverage for both list_id and count, including the hint-like nature of count. The description mostly paraphrases what the schema already states, reinforcing that count is a hint and varies, but it does not add additional meaning beyond the structured schema. Baseline 3 is appropriate.

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 'Preview a sample of rows from a REACH list' and further clarifies that it inspects the actual data rows. This specific verb-resource combination differentiates it from siblings like show_list, which likely shows list metadata or structure rather than row samples.

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

Usage Guidelines4/5

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

The description gives a concise use case: 'Use this tool to inspect the actual data rows in a list.' This provides clear context for when the tool is appropriate. It does not explicitly mention when not to use it or name alternatives, but the usage context is sufficient for a read-only preview tool.

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.

Resources

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