neuron

Bot API Send

neuron_bot_api_send

Send an outbound message through the bot API to a specified phone number. Supports text and media messages. Requires a valid API key.

Input Schema

TableJSON Schema

Name	Required	Description
`to`	Yes	Recipient's phone number (E.164 format, e.g., '+2348012345678')
`apiKey`	Yes	Bot API key with 'nrn_' prefix for authentication
`sendAt`	No	ISO 8601 date-time for scheduled delivery (e.g., '2025-12-31T10:00:00Z'). Message sends immediately if omitted.
`message`	Yes	The message text to send to the recipient
`mediaUrl`	No	Public URL of the media file to attach (required for non-text message types)
`channelId`	No	Unique identifier (UUID) of a specific WhatsApp channel to send from. Uses the bot's primary channel if omitted.
`messageType`	No	Type of message to send: 'text', 'image', 'video', 'audio', or 'document' (default: 'text')

TDQS

A3.6/5.0

Behavior2/5

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

Annotations are all false (readOnlyHint=false, destructiveHint=false), indicating no special behavior. The description adds minimal transparency beyond the obvious write operation ('Send'). It mentions requiring an API key but does not disclose rate limits, failure modes, or security considerations beyond what is in the schema.

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, front-loaded with the core purpose. Every word adds value, and there is no redundant or unnecessary information. It is appropriately sized for the tool's complexity.

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?

Given the tool has 7 parameters, 3 required, and no output schema, the description covers the essential action and supported message types. However, it lacks details on return values or side effects. The annotations provide no additional context, so the description bears the full burden but is mostly adequate.

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 description coverage is 100%, so all 7 parameters are already documented in the input schema. The description adds marginal value by mentioning support for text and media, hinting at messageType and mediaUrl, but does not elaborate on any parameter semantics beyond what the schema provides.

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 'Send', the resource 'outbound message through the bot API', and the scope 'to a specified phone number'. It distinguishes this tool from siblings like 'neuron_send_message' or 'neuron_bot_api_chat' by specifying 'bot API' and mentioning support for text and media messages.

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 context (requires API key) but does not provide explicit guidance on when to use this tool versus alternatives such as neuron_send_message, neuron_bot_api_chat, or other send-related siblings. No exclusions or when-not scenarios are mentioned.

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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