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create_workflow

Build and configure automated workflows by defining pipeline steps, triggers, and actions within the Agentled MCP Server platform.

Instructions

Create a new workflow from a pipeline definition. The pipeline object should include:

  • name (required): Workflow name

  • goal: What the workflow does

  • description: Longer description

  • steps: Array of pipeline steps (trigger, aiAction, appAction, milestone, etc.)

  • context: Execution input config and input/output pages

  • metadata: Template info, notifications, ROI

  • style: UI styling (colors, icon)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipelineYesThe pipeline definition object
localeNoLocale (default: en)

Implementation Reference

  • Tool registration for create_workflow in src/tools/workflows.ts.
        server.tool(
            'create_workflow',
            `Create a new workflow from a pipeline definition. The pipeline object should include:
    - name (required): Workflow name
    - goal: What the workflow does
    - description: Longer description
    - steps: Array of pipeline steps (trigger, aiAction, appAction, milestone, etc.)
    - context: Execution input config and input/output pages
    - metadata: Template info, notifications, ROI
    - style: UI styling (colors, icon)`,
            {
                pipeline: z.record(z.string(), z.any()).describe('The pipeline definition object'),
                locale: z.string().optional().describe('Locale (default: en)'),
            },
            async ({ pipeline, locale }, extra) => {
                const client = clientFactory(extra);
                const result = await client.createWorkflow(pipeline, locale);
                return {
                    content: [{
                        type: 'text' as const,
                        text: JSON.stringify(result, null, 2),
                    }],
                };
            }
        );
  • The handler implementation for create_workflow, which wraps an API request to /api/external/workflows.
    async createWorkflow(pipeline: Record<string, any>, locale?: string) {
        return this.request('/workflows', {
            method: 'POST',
            body: JSON.stringify({ pipeline, locale }),
        });
    }
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 this is a creation operation but doesn't mention permissions required, whether it's idempotent, what happens on failure, or what the response looks like. For a mutation tool with zero annotation coverage, this is a significant gap.

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 efficiently structured as a single sentence followed by a bulleted list of pipeline components. Each bullet point adds specific value about required/optional fields, with no wasted words. However, it could be more front-loaded by explicitly stating the tool's core purpose before diving into details.

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?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like error handling, permissions, or response format. While it details the pipeline structure, it misses critical context needed for safe and effective use by an AI agent.

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 description coverage is 100%, so the schema already documents both parameters ('pipeline' and 'locale'). The description adds value by detailing the structure of the 'pipeline' object (e.g., name, steps, context), but doesn't provide additional syntax or format details beyond what the schema implies. Baseline 3 is appropriate when schema does the heavy lifting.

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 action ('Create a new workflow') and resource ('from a pipeline definition'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'import_workflow' or 'update_workflow', which also involve workflow creation/modification.

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 like 'import_workflow' or 'update_workflow'. It also doesn't mention prerequisites, such as needing a valid pipeline definition or when this operation is appropriate in a workflow lifecycle.

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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