Apply to Sell
neuron_apply_to_sellApply for seller access (digital products). Requires a Pro plan or higher; a platform admin then grants access.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| pitch | No | Short note on what you plan to sell |
neuron_apply_to_sellApply for seller access (digital products). Requires a Pro plan or higher; a platform admin then grants access.
| Name | Required | Description | Default |
|---|---|---|---|
| pitch | No | Short note on what you plan to sell |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only declare the tool is a non-read, non-idempotent operation. The description adds valuable behavioral context: a Pro plan is required, and a platform admin must grant access afterward, indicating this is an application workflow rather than an immediate grant.
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?
Two concise sentences with no filler. The action is front-loaded, and the prerequisite and follow-up behavior are stated in a compact, readable way.
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 one-optional-parameter tool, the description covers eligibility, the application action, and the manual approval step. It does not describe what response the caller should expect, but given the simplicity and absence of an output schema, this is a minor gap.
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 description coverage is 100%, and the single 'pitch' parameter is already documented as a 'Short note on what you plan to sell'. The tool description adds no additional parameter-level guidance beyond the schema, so the baseline score 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?
States a specific verb ('Apply') and resource ('seller access') with a clear qualifier ('digital products'). It is immediately distinguishable from nearby siblings like neuron_seller_status (checking status) and neuron_create_product (creating a product to sell).
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?
Provides clear context: only use if the account has a Pro plan or higher, and access is granted later by an admin. It does not explicitly name alternatives, but the prerequisite condition and manual approval process effectively guide when to call 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.