Skip to main content
Glama
OriginQ

QPanda3 Runtime MCP Server

by OriginQ

list_my_tasks_tool

Retrieve recently submitted quantum computing tasks from the QPanda3 Runtime MCP Server to monitor their status, backend devices, and creation dates.

Instructions

List user's recent tasks.

Retrieve a list of recently submitted quantum computing tasks.

Args: limit: Maximum number of tasks to return (default: 10).

Returns: Dictionary containing: - status: "success" or "error" - tasks: List of task information, each containing: - task_id: Task identifier - status: Current task status - creation_date: When task was created - backend: Target device - total_tasks: Total number of tasks returned

Example: tasks = list_my_tasks_tool(limit=5) for task in tasks["tasks"]: print(f"{task['task_id']}: {task['status']}")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool retrieves 'recent' tasks and includes a default limit, but lacks details on permissions, rate limits, pagination, or error handling. The description adds some behavioral context but is incomplete for a tool with no annotations.

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 sections for purpose, arguments, returns, and an example. It's appropriately sized and front-loaded with the core purpose. Some redundancy exists (e.g., repeating 'list' in the description and example), but overall it's efficient with minimal waste.

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 tool's low complexity (1 parameter, no nested objects) and the presence of an output schema (implied by the detailed return description), the description is reasonably complete. It covers the purpose, parameter, and return format adequately, though it could benefit from more behavioral context given the lack of annotations.

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

Parameters4/5

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

The description adds significant meaning beyond the input schema. The schema has 0% description coverage for the single parameter 'limit', but the description explains it as 'Maximum number of tasks to return (default: 10).' This fully compensates for the schema gap, providing clear semantics for the parameter.

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 tool's purpose: 'List user's recent tasks' and 'Retrieve a list of recently submitted quantum computing tasks.' This specifies the verb (list/retrieve) and resource (tasks), though it doesn't explicitly differentiate from sibling tools like get_task_status_tool or get_task_results_tool. The purpose is clear but lacks sibling differentiation.

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 versus alternatives. It doesn't mention sibling tools like get_task_status_tool or get_task_results_tool, nor does it specify prerequisites, context, or exclusions. The example shows basic usage but offers no strategic advice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/OriginQ/qpanda3-runtime-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server