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aliyun
by aliyun

CreateFunction

Create custom user-defined functions (UDFs) in DataWorks for data development workflows. Define function specifications to extend data processing capabilities within your project.

Instructions

创建数据开发函数

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ProjectIdNoDataWorks工作空间的ID
SpecYes描述这个udf函数的FlowSpec信息
Behavior2/5

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

No annotations are provided, so the description carries full burden. '创建' (create) implies a write operation, but the description doesn't disclose behavioral traits like permissions required, whether it's idempotent, error handling, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence in Chinese ('创建数据开发函数'), which is appropriately sized and front-loaded. There's no wasted text, though it could be more informative. It earns its place but lacks depth.

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?

Given the tool creates a function (a mutation with 2 parameters) and has no annotations or output schema, the description is incomplete. It doesn't cover behavioral aspects, usage context, or what to expect after invocation. For a creation tool in a data development environment, more context is needed to guide the agent effectively.

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 description coverage is 100%, with both parameters (ProjectId and Spec) documented in the schema. The description doesn't add any meaning beyond the schema—it doesn't explain parameter relationships, provide examples, or clarify the Spec format. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description '创建数据开发函数' (Create data development function) states the action (create) and resource (data development function), which is clear. However, it doesn't specify what type of function (UDF) or distinguish it from sibling tools like CreateNode or CreateResource, which also create resources. The purpose is understandable but lacks 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?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a ProjectId), exclusions, or related tools like UpdateFunction or DeleteFunction. The agent must infer usage from the tool name and parameters alone.

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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