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aliyun
by aliyun

TestDataSourceConnectivity

Verify connectivity to data sources in Alibaba Cloud DataWorks by testing connections between specified resource groups and data sources.

Instructions

测试数据源的连通性

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ResourceGroupIdYes资源组ID,即资源组的唯一标识符
DataSourceIdNo待测试连通性的数据源ID,数据源ID是数据源的唯一标识符
ProjectIdNoDataWorks项目空间ID
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. It only states the action ('test connectivity') without disclosing behavioral traits such as whether it's read-only or mutative, what permissions are required, what the output includes (e.g., success/failure details, latency), or any side effects (e.g., logging, triggering alerts). For a tool with no annotation coverage, this is a significant gap.

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 phrase ('测试数据源的连通性') with no wasted words. It's appropriately sized for a simple tool, though it could be more front-loaded with key details if expanded.

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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'testing connectivity' means operationally, what the return values or error conditions are, or how it differs from other data source tools. For a tool with three parameters and potential complexity in testing scenarios, this is inadequate.

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%, so the schema already documents all three parameters (ResourceGroupId, DataSourceId, ProjectId) with descriptions. The tool description adds no additional meaning about parameters, such as how they interact or format specifics. 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.

Purpose2/5

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

The description '测试数据源的连通性' (Test data source connectivity) states the general purpose but is vague. It doesn't specify what 'testing connectivity' entails (e.g., network check, authentication verification, or performance test) or what resource it operates on beyond 'data source'. Compared to siblings like 'GetDataSource' or 'CreateDataSource', it doesn't clearly differentiate its specific action.

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., after creating a data source), exclusions, or related tools like 'GetDataSource' for status checks. The description alone offers no context for appropriate usage scenarios.

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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