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Get Project Data

get_project_data

Fetch project details, uncompleted tasks, and kanban columns in a single request. Use to obtain all active tasks and project structure.

Instructions

Retrieve complete project (清单) data including project details, tasks (任务), and kanban columns (看板列).

WHEN TO USE:

  • Get all uncompleted tasks (未完成任务) within a specific project (清单)

  • Need project metadata AND tasks together

  • View kanban column structure (看板列结构) for kanban-view projects

WHEN NOT TO USE:

  • Only need project metadata → use 'get_project' (faster)

  • Filter tasks by date/priority/across projects (按日期/优先级筛选) → use 'list_tasks'

  • Need completed tasks (已完成任务) → NOT available via API

⚠️ LIMITATION: Only returns UNCOMPLETED tasks (未完成任务, status=0). Completed tasks are not accessible.

RETURNS: { project, tasks[], columns[] } - project metadata (清单信息), task list (任务列表), and kanban columns (看板列).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesThe unique ID of the project to retrieve data for (清单ID)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tasksNo
columnsNo
projectYes
Behavior5/5

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

No annotations provided, so description fully carries behavioral transparency. Discloses limitation that only uncompleted tasks are returned and completed tasks are inaccessible. Mentions return structure.

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

Conciseness5/5

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

Well-structured with sections, front-loaded main purpose, no wasted sentences. Length appropriate for complexity.

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 output schema exists, description provides sufficient context about return data (project, tasks, columns). Covers all relevant behavioral aspects.

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

Parameters3/5

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

Schema coverage is 100% with a single parameter 'projectId' already well-documented. Description adds Chinese terms but does not significantly enhance understanding beyond schema.

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?

Clearly specifies the verb 'Retrieve', resource 'complete project data', and lists sub-resources. Distinguishes from sibling tools like 'get_project' and 'list_tasks' through explicit when-to-use guidance.

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?

Provides explicit 'WHEN TO USE' and 'WHEN NOT TO USE' sections with specific scenarios and alternative tools (e.g., 'get_project' for metadata, 'list_tasks' for filtered tasks). Clearly states limitation about completed tasks.

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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