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create_pipeline

Define a new workflow pipeline DAG with a unique pipeline ID and optional human-readable name, enabling AI agents to build deterministic multi-step data flows.

Instructions

Create a new workflow pipeline DAG with custom identifier and name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoHuman-readable pipeline name.
pipeline_idYesUnique pipeline ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full burden and says nothing about behavior beyond the create verb: no permission requirements, no duplicate/uniqueness handling for pipeline_id, no idempotency, and no mention of what is returned or whether the created pipeline is empty.

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?

A single tight sentence with no filler, and the verb and resource are front-loaded. Nothing is wasted.

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 creation tool with no annotations and no output schema, the description omits key context: uniqueness/duplicate-ID behavior, whether a response object is returned, and how the new pipeline relates to the add_node/connect_nodes/run_pipeline siblings. Two-parameter simplicity makes this survivable but clearly incomplete.

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, making 3 the baseline. The phrase 'custom identifier' mildly adds that pipeline_id is caller-supplied rather than auto-generated, but no format or constraint details go beyond the schema.

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?

Specific verb+resource: 'Create a new workflow pipeline DAG' tells the agent exactly what is produced. It is implicitly distinguishable from siblings like add_node, run_pipeline, and list_pipelines by the create verb, but it never explicitly names or contrasts those siblings.

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?

There is no when-to-use or when-not-to-use guidance, no statement of prerequisites, and no reference to the sibling tools. An agent must infer that this is the entry point before add_node/connect_nodes/run_pipeline.

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