neuron

Merge Contact Lists

neuron_merge_contact_lists

Merge two or more contact lists into a single unified list, deduplicating entries. Window merge creates a virtual union; materialized merge creates a static copy.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Display name for the resulting merged list
`slug`	No	URL-friendly slug for the merged list (auto-generated if omitted)
`mergeType`	Yes	Merge strategy: 'window' (virtual union, stays in sync) or 'materialized' (static copy at merge time)
`sourceListIds`	Yes	UUIDs or slugs of the source lists to merge (minimum 2)

TDQS

A4.4/5.0

Behavior4/5

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

Annotations indicate no read-only or destructive hints, so description carries the burden. It discloses that window merge stays in sync and materialized creates a static copy, but does not specify if source lists are modified or if there are side effects.

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 two sentences with no wasted words. It front-loads the purpose and then explains key distinctions efficiently.

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 description covers core functionality and merge types, but lacks mention of return values (since no output schema) and whether the operation is asynchronous. For a simple tool, it is mostly complete but could include minor additional details.

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

Parameters4/5

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

Schema coverage is 100%, but the description adds value by explaining the behavior of 'window' vs 'materialized' mergeType and the deduplication feature, going beyond the schema's enum descriptions.

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 verb (Merge) and resource (contact lists) with specific action (deduplicating). It distinguishes between window and materialized merge, which differentiates it from sibling tools like create_contact_list or update_contact_list.

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 explains when to use each merge type (window for virtual union, materialized for static copy), providing context. However, it does not explicitly state prerequisites or when to choose this tool over alternatives like creating a new list.

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

B3.4/5.0

Disambiguation3/5

Most tools are clearly separated by resource type, but there is meaningful overlap in messaging entry points (send_message, send_whatsapp, compose_message, bot_api_send) and contact ingestion/sync tools (import_contacts, populate_contacts, sync_whatsapp_contacts). The descriptions help disambiguate, but with 309 tools an agent will frequently need to read closely to pick the right one.

Naming Consistency4/5

The overwhelming majority of tools follow a consistent verb_noun snake_case pattern: create_*, get_*, list_*, update_*, delete_*. Minor deviations like sales_stats, lead_stats, wallet_balance, and whoami break the pattern slightly, but overall naming is highly predictable.

Tool Count1/5

309 tools is an extreme count for any MCP server, even a broad platform. This creates significant cognitive load and navigation overhead for agents, and far exceeds the well-scoped 3-15 tool range where coherence is strongest.

Completeness4/5

The tool surface is remarkably comprehensive across bots, contacts, campaigns, flows, knowledge bases, personas, marketplace, wallet, and products. Minor gaps exist — lead sources lack update/delete tools, and there is no single get_task or get_webhook alongside their list/update/delete counterparts — but these are workable gaps rather than dead ends.

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