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lark-agent

by Wulnut
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

create_task

Create work items or tasks in Feishu/Lark projects by specifying title, priority, assignee, and description. Automate issue creation with optional project and type selection to support project management workflows.

Instructions

在指定项目中创建新的工作项（任务/Issue）。

这是创建飞书项目工作项的主要工具。系统会自动处理字段值的转换
（如将 "P0" 转换为对应的选项 Key）。

Args:
    name: 工作项标题，必填。
    project: 项目标识符（可选）。可以是:
            - 项目名称（如 "SR6D2VA-7552-Lark"）
            - project_key（如 "project_xxx"）
            如不指定，则使用环境变量 FEISHU_PROJECT_KEY 配置的默认项目。
    work_item_type: 工作项类型名称（可选），如 "需求管理"、"Issue管理"、"项目管理" 等名。
                   如不指定，默认使用项目中的第一个可用类型。
    priority: 优先级，可选值: P0(最高), P1, P2(默认), P3(最低)。
    description: 工作项描述，支持纯文本。
    assignee: 负责人的姓名或邮箱。如不指定则为空。
    user_key: (可选) 飞书用户标识符 (X-USER-KEY)，用于以特定用户身份进行操作。

Returns:
    成功时返回 "创建成功，Issue ID: xxx"。
    失败时返回错误信息。

Examples:
    # 使用默认项目创建任务
    create_task(name="修复登录页面崩溃问题", priority="P0")

    # 指定项目和工作项类型创建任务
    create_task(
        project="SR6D2VA-7552-Lark",
        work_item_type="Issue管理",
        name="修复登录页面崩溃问题",
        priority="P0",
        assignee="张三"
    )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
projectNo
assigneeNo
priorityNoP2
user_keyNo
descriptionNo
work_item_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.2

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and performs well: it discloses automatic field-value conversion ('系统会自动处理字段值的转换（如将 P0 转换为对应的选项 Key）'), fallback defaults, and exact return behavior ('创建成功，Issue ID: xxx' on success, error info on failure). It does not cover permission requirements or side effects such as notifications, but the core mutation behavior and automatic transformations are transparent.

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 clear sections — purpose, key auto-conversion behavior, Args list, Returns, and two realistic Examples — and the purpose is front-loaded. It is longer than minimal, but the length is justified by the 0% schema coverage and 7-parameter surface; nearly every sentence earns its place.

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?

For a 7-param creation tool with no annotations and empty schema descriptions, this is nearly complete: purpose, parameter semantics, default behaviors, auto-conversion, and return messages are all covered, and an output schema exists for return values. The one notable omission is user_key semantics, plus there is no guidance on failure scenarios beyond 'returns error info'.

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?

Schema description coverage is 0%, so the description is the sole semantic source, and it compensates strongly for 6 of 7 parameters: project accepts a name or 'project_xxx' key format, priority enumerates P0-P3 with default P2, assignee accepts name or email, description supports plain text, and work_item_type falls back to the first available type. The real gap is user_key, which appears in the schema but is never explained in either the schema or the description.

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 states a specific verb and resource: '在指定项目中创建新的工作项（任务/Issue）' (create new work items in a specified project) and explicitly identifies itself as '创建飞书项目工作项的主要工具' (the main tool for creating Feishu project work items). This role is unambiguous against the sibling set, which contains update/batch_update/get/transition tools but no other creation tool.

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 gives clear usage context: it documents the default project resolution from environment variable FEISHU_PROJECT_KEY, the default work_item_type fallback to the first available type, the default priority P2, and includes two worked examples (minimal default-project call and fully-specified call). However, it never names alternatives or states when NOT to use it, stopping short of explicit exclusion guidance.

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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