Toggle Flow
neuron_toggle_flowEnable or disable a flow. Disabled flows stop receiving events but retain their graph.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | UUID of the flow. | |
| enabled | Yes | true to enable, false to disable. |
neuron_toggle_flowEnable or disable a flow. Disabled flows stop receiving events but retain their graph.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | UUID of the flow. | |
| enabled | Yes | true to enable, false to disable. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With all annotation hints false and no output schema, the description carries most of the behavioral burden and does add useful context: disabling halts event delivery while preserving the graph, so the operation is non-destructive despite being a write. It does not cover auth requirements or what happens on re-enable, but the core side effect is disclosed.
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 short sentences with no filler; the main action is front-loaded and the behavioral caveat is stated immediately. Every clause earns its place.
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 two-parameter state toggle, the description is sufficient to make a correct call: required inputs, the action, and the key behavioral outcome are covered. It omits details about return values or re-enable semantics, but no output schema exists and those are less critical for this operation.
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%: both 'id' and 'enabled' are already documented in the input schema. The description's 'enable or disable' restates the enabled property but adds no parameter-specific detail beyond the schema.
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 action ('Enable or disable') on a concrete resource ('a flow') and clarifies the observable consequence: disabled flows stop receiving events but retain their graph. This distinguishes it from related operations such as deleting, updating, or running a flow.
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 'stop receiving events but retain their graph' clause gives clear context for when to use this tool: the agent wants to change a flow's active state without destroying its structure. It does not explicitly name exclusions or alternatives, but the context is strong enough to guide selection among flow-related siblings.
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.