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deploy_pipeline

Deploy a pipeline to production. Returns validation results or error messages for failed deployments.

Instructions

Deploys a pipeline to production.

This function attempts to deploy the specified pipeline in the given workspace. If the deployment fails due to validation errors, it returns a validation result. :param pipeline_name: Name of the pipeline to deploy.

:returns: Deployment validation result or error message.

The output is automatically stored and can be referenced in other functions. Returns a formatted preview with an object ID (e.g., @obj_123). Use the object store tools in combination with the object ID to view nested properties of the object. Use the returned object ID to pass this result to other functions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pipeline_nameYes
Behavior2/5

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

With no annotations, the description must fully disclose behavior. It mentions that the tool 'attempts to deploy' and returns a validation result on failure, and that output is stored with an object ID. However, it omits critical details: whether deployment is destructive/irreversible, permission requirements, rate limits, or what happens to the previous production pipeline. This is insufficient for a potentially impactful operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is moderately concise with several sentences. It front-loads the main action but includes extraneous details about object store usage that could be omitted or moved. The structure is acceptable but not tight.

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?

Given the critical nature of deployment and the lack of an output schema, the description should explain what 'deploy to production' entails (e.g., whether it overwrites existing). It also fails to mention the missing workspace parameter, leaving a gap. The return value is partially explained, but overall completeness is low for a production deployment tool.

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 coverage is 0% for pipeline_name (no description in schema). The description adds only 'Name of the pipeline to deploy,' which is redundant with the property name and title. It does not specify format, examples, or constraints, providing minimal added value beyond the schema.

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 'Deploys a pipeline to production,' specifying both the action (deploy) and the resource (pipeline). It distinguishes from siblings like deploy_index (deploys index) and create_pipeline (creates, not deploys). The mention of 'to production' adds specificity despite the workspace ambiguity in the parameter list.

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?

No explicit guidance on when to use this tool versus alternatives like deploy_index or validate_pipeline. It does not state prerequisites (e.g., pipeline must exist) or mention that deployment may replace existing production pipelines. The description leaves the agent to infer usage context.

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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