neuron_start_social_channel_sessionStart or reconnect a social media session for the channel. Initializes the platform client with stored credentials.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Unique identifier (UUID) of the social channel to start |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true, which aligns with the description's mention of 'reconnect'. The description adds the detail about initializing with stored credentials, providing context beyond annotations. However, it does not disclose potential side effects or error conditions, so it is adequate but not exceptional.
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 long, directly stating the purpose and behavior. It is concise, front-loaded, and contains no superfluous information.
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 the simple input (one parameter) and no output schema, the description covers the essential behavior. It explains what happens (start/reconnect) and how (initializes with credentials). It could be slightly improved by mentioning the return value or success/failure indicators, but it is largely complete.
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?
There is only one parameter 'id', and the schema already provides a full description ('Unique identifier (UUID) of the social channel to start'). The tool description does not add any additional meaning or context for the parameter beyond that.
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 ('start or reconnect') and the resource ('social media session for the channel'). It also explains the initialization with stored credentials. This effectively differentiates it from sibling tools like 'neuron_stop_social_channel_session' and 'neuron_start_channel_session'.
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 does not explicitly state when to use this tool versus alternatives. The context is implied by the tool name and the mention of 'social channel', but there is no direct guidance on prerequisites or when not to use it.
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.