Delete Persona
neuron_delete_personaDelete a voice persona.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Persona UUID |
neuron_delete_personaDelete a voice persona.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Persona UUID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description says 'Delete a voice persona', which is a destructive action, but the annotation destructiveHint is false. This is a direct contradiction indicating the tool may not be destructive when it actually is. No additional behavioral context is provided beyond the deletion.
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 redundant wording. It efficiently conveys the core purpose without any filler.
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?
The tool is a simple delete operation, but the description lacks essential context about permanence, potential side effects (e.g., impact on bots using the persona), or return values. Given the contradictory annotation and lack of output schema, the description is not sufficiently complete for an agent to fully understand consequences.
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?
The input schema already fully describes the single parameter 'id' as 'Persona UUID', so schema coverage is 100%. The description adds no further meaning to the parameter, matching the baseline of 3 for high schema coverage.
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 'Delete a voice persona' clearly states the action (delete) and the resource (voice persona). It is specific and distinguishes from sibling delete tools by focusing on persona, though it does not explicitly differentiate from other delete_* tools beyond the resource name.
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 usage context is implied: you would use this tool when you want to delete a persona. However, there is no explicit guidance on when to use this versus alternatives like update_persona or build_persona, nor any mention of prerequisites or effects on related entities.
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.