neuron

Create Bot

neuron_create_bot

Create a new AI bot with specified name, model, and behavior instructions. Returns the created bot object.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Display name for the bot
`llmModel`	No	OpenRouter model ID (e.g., 'google/gemini-2.5-flash-lite', 'openrouter/auto')
`metadata`	No	Arbitrary metadata object stored with the bot. Known keys: 'communityExitFollowUp' (auto-DM users who leave watched groups — { enabled: boolean, groupJids: string[], message: string with {name} placeholder }), 'learningConfig' (self-learning from conversations — { enabled: boolean, folder: string, groupChats: string[], dmPhones: string[], useAdminPhones: boolean }), 'loadBalancing' (multi-channel round-robin — { enabled: boolean, strategy: string }), 'welcomeNewMembers' (fine-tune welcome behavior — { batchWindowSeconds: number, groupJids: string[] }). Additional custom keys are preserved as-is.
`maxTokens`	No	Maximum number of tokens the bot can generate per response
`assignment`	No	One-sentence role definition for the bot (max 2000 chars)
`systemPrompt`	Yes	System prompt that defines the bot's behavior, personality, and response guidelines
`llmTemperature`	No	Temperature parameter controlling response randomness (0 = deterministic, 2 = creative)
`welcomeMessage`	No	Welcome message sent to new members joining groups the bot manages. Setting this field activates the batched welcome feature — new members are accumulated over a window (default 60s) and welcomed in a single message with @mentions. Set to null to disable.
`fallbackMessage`	No	Message sent when the bot cannot understand user input (max 2000 chars)
`greetingMessage`	No	Automatic greeting sent when a new conversation starts (max 2000 chars)
`escalationPrompt`	No	Prompt template used when escalating to a human agent (max 5000 chars)
`responsibilities`	No	Array of responsibility descriptions defining what the bot handles
`whatsappChannelId`	No	Unique identifier (UUID) of the WhatsApp channel to associate with the bot

TDQS

B3.4/5.0

Behavior3/5

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

The description discloses that it returns the created bot object, which is useful. However, it does not mention side effects, permissions required, idempotency, or error conditions. With no annotations beyond readOnlyHint=false and destructiveHint=false, the description provides minimal behavioral context beyond the implicit mutation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence of 17 words is concise and front-loads the action. However, it could be slightly improved by including the return value (already present) and hinting at the optional parameters. Still efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 13 parameters, nested objects (metadata with detailed keys), and no output schema, the description adequately states the basic purpose and return value. The schema fills the gaps, but a brief mention of common optional fields would improve completeness. Score 3 is 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 the schema already documents all 13 parameters well. The description only references 'name, model, and behavior instructions' (a subset) without adding new meaning. Baseline 3 is appropriate since the schema does the heavy lifting.

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 'Create a new AI bot' using a specific verb and resource. It mentions key parameters (name, model, behavior instructions) that distinguish it from other creation tools. While it doesn't explicitly differentiate from siblings, the unique resource 'bot' makes purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives such as update_bot, delete_bot, or other create_* tools. There are no prerequisites, exclusions, or context provided to help the agent decide between creating a bot versus other actions.

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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