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Save a pipeline to a YAML file

save_pipeline
Idempotent

Persist a pipeline configuration to a YAML file for reuse or editing, and retrieve the file path to run it later with run.py.

Instructions

Persist a pipeline configuration to a YAML file so it can be reused, edited, or run later with run.py. Returns the path to the written file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
configYes
directoryNopipelines

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4.1/5.0
Behavior4/5

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

With annotations already declaring idempotentHint=true and destructiveHint=false, the description adds value by specifying the output (YAML file) and that it returns the file path. It does not contradict annotations and provides useful detail about the side effect of writing a file.

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?

Two concise sentences with no redundancy. The first sentence immediately states the core action and purpose, and the second adds the return value. All words are necessary.

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 simple nature of a save operation with an output schema already present, the description adequately covers the main aspects. It mentions the return path, which is the key output. The directory parameter is left to schema defaults, and the config object is self-explanatory as a pipeline configuration. No critical information is missing.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate by explaining parameters. It only mentions 'pipeline configuration' and implicitly 'name' and 'directory' through the tool name, but provides no clarification of the config object structure, name requirements, or directory default behavior. The description adds minimal meaning beyond what the schema alone shows.

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 tool's function: 'Persist a pipeline configuration to a YAML file'. It is specific (action: persist, resource: pipeline configuration, format: YAML) and distinguishes itself from sibling tools like export_for_plotjuggler or run_pipeline by focusing on saving the config for later reuse.

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

Usage Guidelines4/5

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

The description provides context on when to use it: 'so it can be reused, edited, or run later with `run.py`'. This clarifies the intended workflow but does not explicitly mention alternatives or when not to use the tool. The contrast with run_pipeline (immediate execution) is implied but not stated.

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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