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get_pipeline

Retrieve the activity list for a specified Azure Data Factory pipeline to inspect its structure and identify steps for monitoring and analysis.

Instructions

Get a single pipeline's activity list.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
factory_nameYes
pipeline_nameYes
resource_groupYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says 'Get', which implies a read operation, but provides no information about authentication requirements, rate limits, side effects, or error behavior. This is a significant gap for a tool with zero annotation coverage.

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

Conciseness2/5

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

The description is a single sentence, which is concise, but it is under-specified rather than appropriately sized. While it is front-loaded with the main purpose, every remaining piece of useful information (usage, parameters, behavior) is absent. This is a case of over-trimming that sacrifices necessary detail.

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?

Although an output schema exists (so return values are covered), the description lacks essential context about what an 'activity list' is, the required Azure Data Factory identifiers, and any operational constraints. Given the tool has three required parameters and no annotation support, the description is incomplete and would leave an agent guessing at invocation details.

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

Parameters1/5

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

Schema description coverage is 0%, meaning the schema provides no semantic explanation for the three required parameters. The description does not mention any of the parameters at all. The parameter names (resource_group, factory_name, pipeline_name) are somewhat self-explanatory, but the description adds no meaning, leaving the agent to guess at concepts like resource_group or factory_name without context.

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?

The description clearly states the action ('Get') and the resource ('a single pipeline's activity list'), and the word 'single' distinguishes it from list operations. However, it doesn't explicitly differentiate from similar siblings like list_activity_runs, and 'activity list' could be ambiguous (definitions vs runs), but the overall purpose is understandable.

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?

The description provides no guidance on when to use this tool instead of alternatives. It doesn't mention any preconditions, exclusions, or scenarios where another tool would be more appropriate. The agent is left to infer usage from the minimal 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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