neuron_update_personaUpdate a persona's name/description, or hand-tune its voiceProfile / exemplars.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Persona UUID | |
| name | No | ||
| exemplars | No | ||
| description | No | ||
| voiceProfile | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already show non-readOnly and non-destructive hints. The description adds the scope of mutations but does not clarify partial vs. full replacement semantics, which would be valuable for nested fields like voiceProfile. It neither contradicts prompts nor provides rich behavioral context.
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?
A single, 15-word sentence that is front-loaded with the verb and target, with no filler or redundancy. Every token adds functional 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?
Although the purpose is clear, the tool has nested objects, no output schema, and minimal annotations. The description does not mention update semantics (e.g., merge vs. replace), prerequisites, or return values, making it incomplete for safe invocation by an agent.
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 only 20% (only 'id' documented). The description references all other parameters and labels voiceProfile/exemplars as 'hand-tune', giving some semantic distinction. However, it does not explain the structure or expected format of these nested objects, leaving meaningful gaps.
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 ('Update'), a clear resource ('persona'), and enumerates the exact fields affected ('name/description', 'voiceProfile / exemplars'). This distinguishes it from sibling tools like neuron_build_persona (creation) and neuron_delete_persona (removal).
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 clearly implies updating an existing persona and specifies the editable components, but it does not explicitly name alternatives or state when not to use it. Context is clear, but no exclusions are provided.
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.