validate_query

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool validates query syntax but doesn't describe what happens during validation - whether it returns errors, warnings, success status, or what format the output takes. For a validation tool with zero annotation coverage, this is a significant gap in behavioral transparency.

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

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

The description is appropriately concise with a clear two-part structure: purpose statement followed by parameter explanations. Each line serves a purpose with no wasted words. The formatting with clear parameter listing makes it easy to scan, though the Chinese-only presentation might limit accessibility in some contexts.

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

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

Given the tool has 4 parameters, no output schema, and no annotations, the description provides basic parameter semantics but lacks important context about what validation entails and what results to expect. For a validation tool that presumably returns validation results, the absence of output information is a notable gap, though the parameter explanations partially compensate.

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

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

The description lists all four parameters with brief explanations in Chinese: '索引名称' (index name), '查询条件' (query conditions), '是否返回详细解释' (whether to return detailed explanation), and '是否返回重写后的查询' (whether to return rewritten query). With 0% schema description coverage, this parameter information is essential and adds meaningful context beyond the bare schema. The explanations clarify what each parameter controls.

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

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

The description states '验证查询语法' (validate query syntax), which clearly indicates the tool's purpose. However, it doesn't specify what type of query or system this validates for, nor does it differentiate from sibling tools like 'explain' or 'search' that might also involve query analysis. The purpose is clear but lacks specificity about scope and differentiation.

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

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. With many sibling tools like 'explain', 'search', and 'search_template' that might overlap with query validation functionality, there's no indication of when validate_query is appropriate versus those other tools. The description is purely functional without usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.