neuron

Create Tool

neuron_create_tool

Create a custom API tool that the bot can invoke during conversations to fetch external data or trigger actions.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	Yes	Human-readable name for the tool
`type`	Yes	Type of the tool integration
`botId`	Yes	Unique identifier (UUID) of the bot to create the tool for
`config`	Yes	Tool configuration specifying the endpoint and request details
`authType`	No	Authentication type for the endpoint
`rateLimit`	No	Maximum number of requests per minute allowed for this tool
`timeoutMs`	No	Request timeout in milliseconds (default: 30000)
`description`	Yes	Description of what the tool does and when the bot should use it

TDQS

B3.4/5.0

Behavior3/5

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

Annotations indicate readOnlyHint=false and openWorldHint=true. The description adds that it creates a tool for bot use, but does not disclose any side effects, limits, or lifecycle implications beyond what annotations already suggest.

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 sentence that clearly conveys the core purpose. It is front-loaded with the action and resource, making it efficient and 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?

The tool has complex nested config and 8 parameters, yet the description provides no information about lifecycle, testing, or how the created tool integrates with the bot. It is insufficient for an agent to fully understand the tool's role in the workflow.

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?

With 100% schema coverage, all parameters are described in the schema. The description adds no additional meaning or context about parameters, so baseline score of 3 applies.

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 it creates a custom API tool for a bot to fetch external data or trigger actions. It uses a specific verb and resource, and distinguishes from other 'create' tools by specifying 'tool' as the resource.

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 explicit guidance on when to use this tool versus alternatives like update_tool or test_tool. It does not mention when not to use it or provide context for selecting this tool over built-in tools.

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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