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get_pipeline_logs

Retrieve detailed logs for any pipeline, with optional filtering by level and pagination for debugging and monitoring.

Instructions

Fetches logs for a specific pipeline.

Retrieves log entries for the specified pipeline, with optional filtering by log level. This is useful for debugging pipeline issues or monitoring pipeline execution. :param pipeline_name: Name of the pipeline to fetch logs for. :param limit: Maximum number of log entries to return (default: 30). :param level: Filter logs by level. If None, returns all levels. :param after: The cursor to fetch the next page of results.

:returns: Pipeline logs 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
limitNo
levelNo
afterNo
Behavior4/5

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

No annotations are provided, so the description carries the burden. It explains output is automatically stored and returns an object ID, which is key behavioral info. It could be more transparent about permissions or format.

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 front-loaded purpose and parameter docs, but has slight redundancy between 'Fetches logs' and 'Retrieves log entries'.

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

Completeness3/5

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

It covers parameters and output usage but lacks details on return format and pagination mechanics (how to get the first cursor). Given no output schema, this is a gap.

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?

Schema description coverage is 0%, but the description fully compensates by explaining each parameter's purpose (pipeline_name, limit, level, after) with clear semantics.

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 'Fetches logs for a specific pipeline' with a specific verb and resource. It distinguishes from siblings as no other tool fetches logs.

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 mentions 'useful for debugging pipeline issues or monitoring pipeline execution', providing clear context. However, it lacks explicit exclusions or alternative comparisons.

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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