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BauplanLabs

Bauplan MCP Server

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by BauplanLabs

get_job

Retrieve job details by ID, including logs, status, and snapshot, to monitor pipeline execution.

Instructions

Retrieve details of a job by job ID, such as user logs, code snapshot, project id. Get details of a specific job by its ID.

Human_readable_status in the response will be "Failed" for failed jobs, "Completed" for completed jobs.

Args: job_id: The ID of the job to retrieve.

Returns: JobInfo: Object containing job details id (str): The ID of the job. kind (str): The kind of job. user (str): The user who created the job. human_readable_status (str): Human-readable status of the job. created_at (Optional[str]): ISO formatted creation timestamp of the job. finished_at (Optional[str]): ISO formatted finish timestamp of the job. status (str): The status of the job. logs (Optional[str]): Concatenated user logs from the job. code_snapshot_path (Optional[Path]): Path to the code snapshot directory. ref (Optional[str]): The data commit reference when the job was run, i.e. the state of source tables for the job at that time. transactional_branch (Optional[str]): The transactional branch that was open when the job was run. project_yml (Optional[str]): The contents of the bauplan_project.yml file from the snapshot. project_files (Optional[dict[str, str]]): A dictionary of other project files from the snapshot, with filenames as keys and file contents as values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
kindYes
userYes
human_readable_statusYes
created_atYes
finished_atYes
statusYes
logsNo
code_snapshot_pathNo
refNo
transactional_branchNo
project_ymlNo
project_filesNo
Behavior4/5

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

No annotations are provided, so the description must stand alone. It describes a read-only operation (retrieve) and details the return fields, including the human_readable_status mapping. While it does not explicitly state that the tool is read-only or that it has no side effects, the action verb 'retrieve' implies a safe operation, and the detailed return spec adds transparency.

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

Conciseness4/5

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

The description is well-structured with a summary, Args, and Returns. It front-loads the main purpose. However, there is minor redundancy: the first two sentences both convey 'get details of a specific job by its ID.' Trimming this would improve conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no annotations, existing output schema), the description provides complete context. It explains the job retrieval, the meaning of human_readable_status, and lists all return fields with types and descriptions. An agent can fully understand the tool's behavior without additional information.

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

Parameters5/5

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

The input schema has one required parameter (job_id) with no description. The description fills this gap with an Args section: 'job_id: The ID of the job to retrieve.' This adds full meaning beyond the schema, achieving high semantic value despite the schema's 0% coverage.

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 purpose: 'Retrieve details of a job by job ID.' It specifies what the tool does (retrieve details) and the resource (job by ID). Among sibling tools like list_jobs or cancel_job, this is distinct and unambiguous.

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 effectively communicates when to use the tool (when you have a job ID and need full details). Although it does not explicitly exclude alternatives, the context of sibling names like list_jobs and cancel_job makes the usage context clear. Missing explicit 'when not to use' guidance prevents a 5.

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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