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add_step

Register or update a pipeline step in the ML workflow DAG by name, defining its inputs, outputs, parameters, and script path.

Instructions

Register a pipeline step (a node on the map), or update it if the name already exists.

Input Schema

NameRequiredDescriptionDefault
nameYesUnique step name, e.g. 'load_smiles', 'split', 'train_gcn'
inputsNoData this step consumes, e.g. ['graphs.pkl']
paramsNoDefault parameters, e.g. {'test_size': 0.2, 'seed': 42}
outputsNoData this step produces, e.g. ['train.pkl', 'test.pkl']
descriptionNoOne-line description of what the step does
script_pathNoPath of the step's Python script, relative to the project root

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses that an existing name is updated rather than rejected, but is silent on what an update replaces (are stale inputs/outputs/params discarded or merged?) and on whether the step is persisted immediately.

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 front-loaded sentence with zero filler; the upsert caveat is placed where it will be read.

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?

With a rich six-parameter schema and an output schema present, the description need only cover intent and side effects. Intent and upsert semantics are covered; the only real gap is the precise overwrite/merge semantics of the update path.

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% and every parameter carries a concrete example, so the schema does the heavy lifting. The description adds no extra meaning about parameter interaction, such as whether outputs must match a downstream step's inputs.

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?

States a specific verb and resource ('Register a pipeline step') plus the domain framing ('a node on the map'). It also discloses the upsert behavior, which distinguishes it from a pure create. It doesn't explicitly contrast with sibling connect_steps, but the resource distinction is inferable.

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 statement of when to call this versus connect_steps, get_pipeline, or init_project, and no prerequisites (e.g., must a project exist first?). The only guidance is implicit in the upsert clause.

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