company_lists-count_preview
Estimate how many companies match a list filter and how many credits the list operation would cost.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| __requestBody | Yes | Request body |
Saber
TDQS
B3.2/5.0
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description presents a preview/estimation operation, which strongly implies read-only behavior, but the annotations declare readOnlyHint=false. This is an annotation contradiction. The description also does not explain whether credits are consumed by the preview itself, what side effects might occur, or how the open-world nature affects the estimate.
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. It efficiently communicates the two key outputs: company count estimate and credit cost estimate.
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?
Despite having no output schema, the description does not explain the return format or whether the tool returns both count and cost separately. It also omits when to use the preview versus actual list operations, and the readOnlyHint contradiction leaves behavioral expectations unclear. Given the nested filter complexity, more context is needed.
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 each filter property has its own description with examples. The tool description adds nothing beyond the phrase 'list filter,' so it does not improve on what the schema already provides. 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 a specific action (estimate) and resource (companies matching a list filter), and adds the unique aspect of credit cost estimation. This distinguishes it from sibling tools like company_lists-get_companies or company_lists-export, which perform actual retrieval/export operations.
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 'would cost' implies this tool is meant to be used before an actual list operation to preview counts and credits, but it never explicitly says 'use before creating/exporting a list' or contrasts itself with alternatives. Usage context is only implied, not stated.
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
C2.5/5.0
Disambiguation2/5
Many tools have overlapping purposes, such as signals-firmographics vs companies-enrich_firmographics, findEmail vs contacts-enrich_work_email, and monitors vs signal_subscriptions vs market_signals. While descriptions add some context, an agent could easily select the wrong tool due to the high similarity in function.
Naming Consistency2/5
Most tools use a resource_subresource-action pattern, but there are inconsistent separators: underscores within some names, hyphens in others (e.g., scoring-assignment-bulk-create), and several camelCase exceptions (findEmail, findEmailBatchGet, getContactResearchByExternalID). This mixed convention makes the tool set feel unpredictable.
Tool Count1/5
With 119 tools, this server vastly exceeds the typical well-scoped range. Even for a comprehensive B2B data platform, the sheer number creates cognitive overload and increases the risk of incorrect tool selection.
Completeness4/5
The server covers an extensive range of operations: enrichment, lists, contacts, signals, subscriptions, monitors, and scoring. Nearly every resource has create, read, update, and delete or lifecycle equivalents, leaving very few practical gaps for the intended use case.