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aliyun
by aliyun

DeleteDataQualityRule

Remove a data quality rule from your DataWorks project to maintain clean data governance and eliminate outdated validation criteria.

Instructions

删除质量规则

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
IdNo规则ID
ProjectIdNoDataWorks工作空间ID
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states '删除质量规则' (Delete quality rule), which implies a destructive operation but provides no information about permissions required, whether deletion is permanent or reversible, what side effects occur, rate limits, or error conditions. For a destructive tool with zero annotation coverage, this is critically insufficient.

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

Conciseness2/5

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

While technically concise with just three Chinese characters, this is under-specification rather than effective conciseness. The description fails to provide necessary information about a destructive operation, making it inefficient rather than appropriately brief. Every sentence should earn its place, but here the single phrase doesn't earn its place by providing adequate guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a destructive operation with no annotations and no output schema, the description is completely inadequate. It doesn't explain what happens after deletion, what permissions are required, whether the action is reversible, or what the response looks like. For a tool that permanently removes data quality rules, this minimal description creates significant risk of misuse.

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 (Id and ProjectId) documented in the schema. The description adds no parameter information beyond what the schema already provides. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

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 '删除质量规则' (Delete quality rule) is a tautology that restates the tool name in Chinese without adding specificity. It doesn't clarify what type of quality rule, what system it operates in, or what distinguishes it from similar deletion tools like DeleteAlertRule or DeleteDataQualityEvaluationTask. The description merely translates the name without providing meaningful context about the action's scope or target.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

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. There are multiple deletion tools in the sibling list (e.g., DeleteAlertRule, DeleteDataQualityEvaluationTask, DeleteDataServiceApi), but the description doesn't indicate when this specific deletion is appropriate, what prerequisites exist, or what happens after deletion. No contextual usage information is provided.

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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