get_vector_database_stats

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. While it mentions the tool returns detailed statistics, it doesn't specify whether this is a read-only operation, what permissions might be required, potential rate limits, or how the statistics are formatted. For a tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed.

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 well-structured with clear sections: purpose statement, usage scenarios, and return information. It's appropriately sized for a zero-parameter tool. The only minor issue is some redundancy between the purpose statement and return section, but overall it's efficient and front-loaded.

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 that the tool has an output schema (which handles return value documentation) and zero parameters, the description provides adequate context about purpose and usage scenarios. However, with no annotations and multiple sibling statistics tools, it could benefit from more differentiation and behavioral details to be fully complete.

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 tool has 0 parameters with 100% schema description coverage (empty schema). The description doesn't need to explain any parameters, which is appropriate. It correctly focuses on what the tool does rather than parameter details, earning a high score for this dimension.

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 the tool '获取向量数据库的详细统计信息' (gets detailed statistics of the vector database), which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'get_knowledge_base_stats' or 'get_embedding_cache_stats', leaving ambiguity about what distinguishes these statistics tools. The purpose is understandable but lacks sibling 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 includes a '使用场景' (usage scenarios) section listing four specific contexts: checking database status, analyzing document distribution, diagnosing performance issues, and planning optimization. This provides clear guidance on when to use the tool. However, it doesn't explicitly state when NOT to use it or mention alternatives among siblings, which prevents a perfect score.

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