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Create Bot Task

neuron_create_task

Create a scheduled autonomous task for a bot. The instruction is a self-contained, natural-language directive the bot executes with its tools (find stale conversations, message contacts, schedule follow-ups, etc.). Sends are always screened against Do-Not-Contact, a per-run cap, and a no-repeat window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
botIdYesUUID of the bot
titleYesShort title for the task
configNoSafety / execution config for the task.
enabledNoWhether the task is active (default true).
scheduleNoSchedule payload matching scheduleKind. cron: { time: 'HH:MM', days?: number[] } (0=Sunday..6=Saturday; empty/omitted = every day). interval: { everyMinutes: number }. once: { runAt: ISO8601 string }. manual: {}.
timezoneNoIANA timezone (e.g. Africa/Lagos). Defaults to UTC.
instructionYesWhat the task should do, in natural language (self-contained; preserve any exact message copy verbatim).
scheduleKindYescron = recurring at a clock time (slot); interval = every N minutes; once = a single future moment; manual = only runs on demand.

TDQS

A4.4/5.0
Behavior4/5

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

Beyond the annotations (all false, indicating a write operation that is not idempotent), the description adds valuable behavioral context: 'Sends are always screened against Do-Not-Contact, a per-run cap, and a no-repeat window.' This discloses safety guardrails and how the bot executes the instruction with its tools. No contradiction with annotations.

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 verb+resource. The first sentence states the purpose, and the second adds meaningful examples and safety constraints. No filler or repetition of schema information.

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's complexity (8 parameters, nested objects, and no output schema), the description covers the essential concept and safety behavior. It does not mention return values, but for a create operation with comprehensive schema documentation, this is not a critical gap. The description is sufficiently complete for an agent to understand the tool's role.

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?

The input schema already has 100% parameter description coverage, so the baseline is 3. The description adds meaning by clarifying that 'instruction' is a self-contained, natural-language directive and gives concrete examples of what it can include. This extra context helps agents construct valid instructions without relying solely on the schema.

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 opens with 'Create a scheduled autonomous task for a bot,' which identifies the specific action (create), resource (task), and scope (scheduled, autonomous, for a bot). It clearly distinguishes this from sibling tools like run_task or update_task. The additional detail about natural-language instructions reinforces what the tool does without ambiguity.

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 provides clear context for when to use this tool: it is for scheduling autonomous bot tasks, with examples of instructions such as 'find stale conversations' and 'message contacts.' It does not explicitly name alternatives or exclusions, but the context sufficiently differentiates it from one-off send tools or manual run 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.

Resources