sql_query

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool executes SQL queries and shows parameter usage, but doesn't describe important behaviors: whether queries are read-only or can modify data, authentication requirements, rate limits, timeout behavior, error handling, or result pagination beyond fetch_size. For a SQL execution tool with zero annotation coverage, this is inadequate.

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 for description, parameters, and examples. It uses minimal Chinese text efficiently. However, the parameter explanations could be more concise, and the examples section could be integrated more tightly with the parameter descriptions.

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?

For a SQL execution tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It covers basic parameter semantics and shows examples, but misses critical context: what SQL dialect is supported, whether DML/DDL queries are allowed, transaction behavior, connection requirements, error formats, and result structure. The absence of output schema means the description should explain return values but doesn't.

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?

Schema description coverage is 0%, so the schema provides no parameter documentation. The description lists all three parameters with brief explanations: 'SQL 查询语句' (SQL query statement), '返回格式 json/csv/txt/yaml' (return format), and '每次获取的行数' (rows fetched each time). This adds meaningful semantics beyond the bare schema, but doesn't provide format details, fetch_size constraints, or query syntax guidance. Examples show query usage but not format/fetch_size usage.

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 clearly states '执行 SQL 查询' (execute SQL query), which is a specific verb+resource combination. It distinguishes itself from sibling tools like 'search' or 'aggregate' by focusing on raw SQL execution rather than Elasticsearch-specific query DSL. However, it doesn't explicitly contrast with SQL-like alternatives in the sibling list.

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 like 'search', 'aggregate', or 'count'. There's no mention of prerequisites, performance considerations, or limitations. The examples show basic SQL queries but don't explain context for choosing SQL over native Elasticsearch APIs.

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