Update Profile Status
neuron_update_profile_statusUpdate the bot's WhatsApp status/bio text.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| status | Yes | New status/bio text | |
| channelId | Yes | WhatsApp channel identifier (UUID) |
neuron_update_profile_statusUpdate the bot's WhatsApp status/bio text.
| Name | Required | Description | Default |
|---|---|---|---|
| status | Yes | New status/bio text | |
| channelId | Yes | WhatsApp channel identifier (UUID) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate idempotentHint=true, readOnlyHint=false, etc. The description adds no behavioral context beyond stating 'update'. It does not disclose what happens if the status is too long, whether it overrides previous text, or if there are rate limits.
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 a single, front-loaded sentence with no extraneous information. Every word contributes to clarity.
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?
For a simple two-parameter tool with no output schema, the description covers the basic purpose but omits potential constraints (e.g., max length, idempotency implications). It lacks sibling differentiation, which would improve completeness.
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% for both parameters, so the description need not add much. However, it does not clarify parameter semantics beyond the schema (e.g., that 'status' is a free-text string with no format restrictions). Baseline 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 ('update'), the resource ('the bot's WhatsApp status/bio text'), and is specific. It distinguishes from sibling tools like neuron_update_profile_name and neuron_update_profile_picture, which change different profile fields.
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?
No guidance on when to use this tool versus alternatives. With many sibling update tools, the description should indicate when this is appropriate (e.g., for WhatsApp status only) and mention exclusions, but it does not.
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.