List Leads
neuron_list_leadsList leads from the pool, filterable by status (new/enriched/contacted/converted/rejected), sourceId, and search.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| search | No | ||
| status | No | ||
| sourceId | No |
neuron_list_leadsList leads from the pool, filterable by status (new/enriched/contacted/converted/rejected), sourceId, and search.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| search | No | ||
| status | No | ||
| sourceId | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that leads are drawn from 'the pool' and are filterable, but discloses no additional behavioral traits like pagination defaults, sorting, or result 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?
Single sentence, front-loaded with the action and object, and compactly conveys filters. No filler or redundant 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?
With 5 parameters and no output schema, the description covers the core filters but leaves pagination parameters unexplained and does not describe the return shape or default behavior. It is adequate for a simple list operation but has room for more detail.
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 has zero property descriptions, so the description must compensate. It adds meaning to 'status' by enumerating the allowed values (new/enriched/contacted/converted/rejected) and identifies sourceId and search as filters, but omits any explanation for page and limit, which remain undocumented.
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 uses a specific verb 'List' with a clear resource 'leads from the pool' and enumerates filter dimensions (status, sourceId, search). This distinguishes it from sibling tools like list_contacts or list_lead_sources.
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 usage context by listing available filters, but provides no explicit guidance on when to prefer this over alternatives or any exclusions. It does not mention related tools such as lead_stats or pool browsing, leaving selection to the agent's inference.
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.