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Run Flow

neuron_run_flow

Manually trigger a flow run for testing. Starts at the 'trigger.manual' node if present, otherwise the first trigger node. Optionally provide a payload object that becomes {{trigger.*}} in the flow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUUID of the flow to run.
nodeIdNoSpecific trigger node id to start from (for flows with multiple triggers).
payloadNoTest payload available as {{trigger.*}} in the flow — e.g. { text: 'hello', contactPhone: '2348012345678', senderName: 'Test User' }.

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations, the description explains important runtime behavior: which node execution starts at and how the payload is exposed to the flow. This adds meaningful context about what happens when the tool is invoked, though it does not mention return behavior or asynchronous execution.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short, purposeful sentences. The primary action is stated first, followed by start-node behavior and payload semantics, with no filler or repeated schema content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a testing/trigger action, the description covers the core invocation details: what starts, where it starts, and how payload is passed. The lack of any return-value or run-completion information is a minor gap given the tool's purpose, and the schema covers the required parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already documents all three parameters. The description reinforces the payload-to-{{trigger.*}} mapping that the schema already provides, but adds no significant extra meaning for id or nodeId beyond what the schema states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('trigger'), a clear resource ('a flow run'), and a clear intent ('for testing'). It also describes the execution start behavior, which distinguishes it from operations like listing, getting, or canceling flow runs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Manually trigger for testing' gives clear context for when this tool is appropriate. It does not explicitly name alternatives or exclusion criteria, but the manual-testing framing provides enough situational guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation3/5

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.

Naming Consistency4/5

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.

Tool Count1/5

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.

Completeness4/5

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.

Resources