Skip to main content
Glama
Livus-AI
by Livus-AI

execute_workflow

Run a named workflow script with optional parameters to automate tasks and processes programmatically.

Instructions

Execute a workflow script by name.

Args:
    name: The name of the workflow to execute
    params: Optional dictionary of parameters to pass to the workflow's run() function

Returns:
    dict: The result of the workflow execution

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
paramsNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool executes a workflow and returns a result, but lacks details on permissions needed, side effects (e.g., whether execution is logged or affects system state), error handling, or performance implications. This is inadequate for a mutation tool with zero annotation coverage.

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 front-loaded with the core purpose in the first sentence, followed by structured Arg and Return sections. Each sentence earns its place by defining parameters and output without redundancy. It's appropriately sized and well-organized for clarity.

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 complexity of executing workflows, lack of annotations, no output schema, and 2 parameters with nested objects, the description is incomplete. It doesn't explain what a 'workflow' entails, potential risks, authentication needs, or the format of the returned dict. More context is needed for safe and effective use.

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

Parameters4/5

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

The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'name' identifies the workflow to execute and 'params' is an optional dictionary passed to the workflow's run() function, clarifying usage and intent. This compensates well for the schema's lack of descriptions, though it doesn't detail param structure or constraints.

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 verb 'execute' and resource 'workflow script by name', making the purpose evident. It distinguishes from siblings like create_workflow or list_workflows by focusing on execution rather than CRUD operations. However, it doesn't explicitly differentiate from potential alternatives like 'run_workflow' if they existed, keeping it at 4 instead of 5.

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. It doesn't mention prerequisites (e.g., workflows must exist), exclusions, or comparisons to sibling tools like update_workflow or read_workflow. Usage is implied through the action but lacks explicit context for selection.

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/Livus-AI/Skills-MCP'

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