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Livus-AI
by Livus-AI

create_workflow

Create Python workflow scripts with a run function for automation tasks, enabling AI agents to build and modify automation workflows programmatically.

Instructions

Create a new Python workflow script.

Args:
    name: The name of the workflow (will be used as filename, e.g., "meeting_review_to_slack")
    description: A description of what the workflow does
    code: The Python code for the workflow. Must include a `run(params: dict = None) -> dict` function.

Returns:
    dict: Status of the operation with the file path

Example code structure:
    def run(params: dict = None) -> dict:
        params = params or {}
        # Your workflow logic here
        return {"status": "success", "result": "..."}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionYes
codeYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool creates a file and returns a status with a file path, adding useful context beyond basic functionality. However, it doesn't cover critical behavioral traits like error handling, authentication needs, or rate limits, leaving gaps for a mutation tool.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded, starting with the core purpose followed by detailed parameter explanations and an example. While efficient, the example code could be slightly trimmed, but overall, each sentence adds value without unnecessary fluff.

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

Completeness3/5

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

Given the tool's complexity as a mutation tool with no annotations and no output schema, the description is moderately complete. It covers parameters well and provides an example, but lacks details on return values beyond a vague 'status', error cases, or integration with sibling tools, leaving room for improvement.

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

Parameters5/5

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

The description adds significant meaning beyond the input schema, which has 0% coverage. It explains that 'name' is used as a filename with an example, 'description' clarifies its purpose, and 'code' specifies required Python structure including a 'run' function, effectively documenting all three parameters where the schema does not.

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 'Create' and the resource 'new Python workflow script', making the purpose evident. However, it doesn't explicitly differentiate from siblings like 'update_workflow' or 'read_workflow', which would require mentioning this is for initial creation only.

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?

No guidance is provided on when to use this tool versus alternatives like 'update_workflow' or 'execute_workflow'. The description implies usage for creating workflows but lacks explicit context or prerequisites, such as whether it overwrites existing workflows or requires specific permissions.

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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