Skip to main content
Glama

run_flow_advanced

Execute Langflow workflows with advanced control: configure tweaks, input/output types, session persistence, and streaming for customized flow execution.

Instructions

Advanced flow execution with full parameter control including tweaks, input/output types, session management, and streaming. Supports both flow UUID and flow name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
streamNoEnable streaming mode (default: false)
tweaksNoComponent-specific parameter overrides
user_idNoUser ID (UUID) for user-scoped execution
input_typeNoType of input (e.g., "chat", "text")
session_idNoSession ID for conversation continuity
input_valueNoInput value for the flow
output_typeNoExpected output type (e.g., "chat", "text", "json")
flow_id_or_nameYesFlow ID (UUID) or flow name to execute
output_componentNoSpecific output component to retrieve results from
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions capabilities but does not describe side effects (e.g., state changes), error behavior, authentication needs, or defaults. For a complex execution tool, this is insufficient for an agent to anticipate behavior.

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?

The description is extremely concise: two sentences covering all major capabilities. It is front-loaded with the core purpose and immediately follows with the identifier support detail. No extraneous words or repetition.

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

Completeness2/5

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

Given the tool's complexity (9 parameters, nested objects, no output schema), the description lacks critical context. It does not explain return values, error conditions, or how to use parameters together. An agent would need more information to invoke this tool correctly.

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 description does not need to explain parameter meaning in detail. The description reinforces categories like tweaks and streaming but adds no additional semantic value beyond the schema. This meets the baseline for high coverage.

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

Purpose4/5

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

The description clearly states the tool's purpose: advanced flow execution with full parameter control. It mentions specific features like tweaks, input/output types, session management, and streaming. However, it does not explicitly differentiate from similar sibling tools like 'run_flow', relying on the name 'advanced' to imply distinction.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives such as 'run_flow' or 'run_flow_session'. There are no prerequisites, constraints, or scenarios where the tool is not appropriate, leaving the agent without decision-making context.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/nobrainer-tech/langflow-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server