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get_step_schema

Retrieve the complete schema of allowed fields for workflow steps to understand configurable parameters and ensure only valid data is persisted.

Instructions

Get the full schema of allowed fields on workflow steps (PipelineStep type). Returns field names, types, descriptions, grouped by category. Use this to understand what fields you can set on a step. Unknown fields are automatically stripped on save — only fields listed here are persisted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Registration of the get_step_schema tool in the MCP server.
        server.tool(
            'get_step_schema',
            `Get the full schema of allowed fields on workflow steps (PipelineStep type).
    Returns field names, types, descriptions, grouped by category. Use this to understand what fields you can set on a step.
    Unknown fields are automatically stripped on save — only fields listed here are persisted.`,
            {},
            async (_args, extra) => {
                const client = clientFactory(extra);
                const result = await client.getStepSchema();
                return {
                    content: [{
                        type: 'text' as const,
                        text: JSON.stringify(result, null, 2),
                    }],
                };
            }
        );
  • The actual handler implementation in the AgentledClient class, which makes a request to the API.
    async getStepSchema() {
        return this.request('/workflows/step-schema');
    }
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It effectively discloses key behavioral traits: it's a read-only operation (implied by 'Get'), returns structured schema data, and warns about automatic stripping of unknown fields on save. However, it doesn't mention potential errors, rate limits, or authentication needs, leaving some gaps.

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 usage guidance and a critical warning. Every sentence earns its place: the first defines the tool, the second instructs when to use it, and the third explains a key behavioral consequence. No wasted words.

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?

Given the tool's complexity (simple read operation with 0 parameters) and lack of annotations/output schema, the description is nearly complete. It covers purpose, usage, and a critical behavioral note. However, it could briefly mention the return format (e.g., JSON structure) or error cases for full completeness, as there's no output schema to rely on.

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 tool has 0 parameters with 100% schema description coverage. The description doesn't need to explain parameters, but it correctly implies none are required by not mentioning any. It adds value by clarifying the tool's purpose and output, aligning with the baseline expectation for zero-parameter tools.

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 clearly states the specific action ('Get the full schema'), the resource ('workflow steps (PipelineStep type)'), and the output content ('field names, types, descriptions, grouped by category'). It distinguishes itself from siblings like 'get_workflow' or 'update_step' by focusing on schema metadata rather than workflow instances or step updates.

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

Usage Guidelines5/5

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

It explicitly states when to use this tool: 'Use this to understand what fields you can set on a step.' It also provides a critical exclusion: 'Unknown fields are automatically stripped on save — only fields listed here are persisted,' guiding users to consult this schema before setting step fields to avoid data loss.

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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