neuron_unassign_bot_from_social_channelRemove the bot assignment from a social media channel. The bot will lose access to the channel's social media credentials.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Unique identifier (UUID) of the social channel to unassign the bot from | |
| botId | Yes | Unique identifier (UUID) of the bot to unassign |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context beyond annotations: 'The bot will lose access to the channel's social media credentials' explains the destructive effect indicated by 'destructiveHint': true. It aligns with annotations and provides meaningful behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, concise and front-loaded. Every word is necessary; no fluff. It efficiently conveys the purpose and effect.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description sufficiently explains the tool's effect on the bot's access. It could be improved by confirming the result (e.g., 'Returns success status'), but it is complete for a straightforward unassignment operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described clearly (UUIDs for channel and bot). The tool description adds no additional meaning beyond what the schema already provides, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Remove the bot assignment from a social media channel' with a specific verb and resource. It distinguishes itself from siblings like 'neuron_assign_bot_to_social_channel' and 'neuron_unassign_bot_from_channel' by specifying 'social channel'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when needing to remove bot assignment from a social channel) but does not explicitly exclude alternatives or provide context for when not to use it. Siblings like 'neuron_unassign_bot_from_channel' exist but are not mentioned, leaving potential ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.