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adamstuber

uipath-orchestrator-mcp

by adamstuber

get_queue_items

Retrieve a batch of UiPath Orchestrator queue items with optional OData filters, pagination, and sorting. Fetch specific items by status, priority, or reference to process or monitor queues.

Instructions

Retrieve a batch of queue items from a specific queue.

Queue item statuses: New, InProgress, Successful, Failed, Abandoned, Retried, Deleted.

Before calling this on a large queue, use count_queue_items to check volume. Use most_recent_first=True with a small batch_size to efficiently get the latest items.

OData filter examples:

  • "Status eq 'Failed'"

  • "Status eq 'New' and Priority eq 'High'"

  • "Reference eq 'ORDER-123'"

Args: folder_name: The display name of the folder. queue_name: The name of the queue. batch_size: Number of items to return (default 100). skip: Number of items to skip for pagination (default 0). filter_query: Optional OData filter string. most_recent_first: If True, return newest items first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNo
batch_sizeNo
queue_nameYes
folder_nameYes
filter_queryNo
most_recent_firstNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description must carry the full weight. It implies read-only via 'Retrieve' and discloses statuses, OData filtering, pagination, and ordering options. However, it does not explicitly state that no mutations occur, nor does it mention permissions, rate limits, or error behavior, leaving some gaps.

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: a clear one-sentence purpose, status list, usage tips, filter examples, then parameter definitions. It is a bit long but every sentence adds value, and the key purpose is front-loaded.

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 complexity (6 parameters, filtering, pagination, sorting) and the presence of an output schema, the description covers purpose, usage, parameters, and examples. It omits error handling and permission details, but the output schema handles return values, making it reasonably complete.

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 schema has 0% description coverage, but the description's 'Args' section explains every parameter in plain language, including defaults and filter_query semantics with concrete OData examples. This fully compensates for the schema gap.

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 'Retrieve a batch of queue items from a specific queue,' which is a specific verb+resource+scope statement. It distinguishes from sibling tools like count_queue_items (counting) and add/delete/retry (mutations).

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

Usage Guidelines5/5

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

It explicitly tells the agent to use count_queue_items before calling this on a large queue, providing both an alternative and a when-not-to-use scenario. It also recommends most_recent_first=True with a small batch_size for efficiency, giving actionable usage advice.

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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