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companies-enrich_custom_batch

Enrich many companies with one custom question

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
__requestBodyYesRequest body

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already disclose readOnlyHint=false, destructiveHint=false, and idempotentHint=false, so the description's job is lighter. It adds context about batch size ('many companies') and custom questions, but doesn't mention asynchronous behavior, webhook usage, or that 'question' is optional. 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 with no filler. It conveys the core purpose immediately and is easy to parse.

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 complex nested request body (many optional fields), no output schema, and vague annotations, the description is insufficient. It doesn't hint at batch limits (max 100 targets), webhook callbacks, or async behavior, and misleadingly implies 'one custom question' is required when only 'targets' is required. More context is needed for an agent to invoke 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 description maps 'many companies' to the 'targets' array and 'custom question' to the 'question' field, giving some semantic anchor. However, the schema already describes 'targets', and many other nested fields (answerType, connectors, webhookUrl, forceRefresh, etc.) are left unexplained. With high schema coverage, a baseline of 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 uses a specific verb 'Enrich' plus a clear resource scope: 'many companies' with 'one custom question'. This distinguishes it from sibling tools like companies-enrich_custom (single company) and other enrich types such as firmographics or funding.

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 phrase 'many companies' clearly indicates this is for batch enrichment, implying use when multiple companies need the same custom question. It does not explicitly name alternatives or exclusions, but the batch context is evident from the sibling tool 'companies-enrich_custom'.

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.

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