neuron

Submit List to Pool

neuron_submit_to_list_pool

Submit a contact list to the shared pool marketplace for other organizations to discover and use for ad distribution.

Input Schema

TableJSON Schema

Name	Required	Description
`listId`	Yes	Unique identifier (UUID) of the contact list to submit
`category`	Yes	Audience category (e.g., 'delivery', 'tech', 'consumers', 'food')
`channelId`	Yes	Unique identifier (UUID) of the WhatsApp channel used for sending messages
`description`	No	Human-readable description of the audience and its characteristics
`demographics`	No	Demographic information about the contact list audience
`pricePerDelivery`	Yes	Price per successful message delivery in kobo (e.g., 5000 = NGN 50)

TDQS

B3.4/5.0

Behavior2/5

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

With no annotations providing safety info, the description carries the full burden. It says 'submit' but does not disclose side effects (e.g., whether the list is removed from owner), permissions needed, or reversibility. It lacks sufficient behavioral context for a write operation.

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, clear sentence with no wasted words. It is front-loaded and efficient.

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 6 parameters (4 required) and no output schema, the description is incomplete. It does not explain the return value or success criteria, nor does it mention the process (e.g., approval, immediate availability). Important context for a marketplace submission is missing.

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%, so baseline is 3. The description does not add meaning beyond the schema's parameter descriptions. It lists no parameter-specific guidance or examples.

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 'submit', the resource 'contact list', and the context 'shared pool marketplace for other organizations to discover and use for ad distribution'. It effectively distinguishes this tool from siblings like 'neuron_browse_list_pool' and 'neuron_install_from_pool'.

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 description implies usage for sharing a list, but does not explicitly state when to use this tool versus alternatives like 'neuron_publish_to_pool' or 'neuron_update_pool_item'. No when-not-to-use or exclusion criteria are provided.

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.

Resources

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