execute_sql

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 mentions support for multiple SQL statements separated by semicolons, which adds some context beyond the basic 'execute SQL' purpose. However, it fails to disclose critical behavioral traits such as whether this is a read/write operation, potential side effects (e.g., data modification), authentication requirements, error handling, or rate limits. For a database tool with mutation potential, 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.

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

The description is extremely concise and front-loaded: a single sentence that directly states the tool's purpose and key capability (support for multiple statements). There is no wasted verbiage, and every word earns its place by conveying essential information efficiently.

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 complexity of a database SQL execution tool with no annotations and no output schema, the description is incomplete. It lacks information about return values (e.g., result sets, error messages), behavioral constraints (e.g., read-only vs. write operations, transaction handling), and how it differs from sibling tools. For a tool that could perform destructive operations, this is inadequate.

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 schema description coverage is 100%, with the single parameter 'query' documented as '要执行的SQL语句' (SQL statement to execute). The description adds minimal value beyond the schema by implying the query can contain multiple statements separated by semicolons, but it doesn't elaborate on syntax, constraints, or examples. Given the high schema coverage, the baseline score of 3 is appropriate.

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 the tool's purpose: '在MySQL数据库上执行SQL' (execute SQL on MySQL database). It specifies the verb ('执行' - execute) and resource ('SQL'), and mentions support for multiple statements separated by semicolons. However, it doesn't explicitly differentiate from sibling tools like optimize_sql or get_table_name, which prevents a score of 5.

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. It doesn't mention when to use execute_sql versus optimize_sql (for optimization) or get_table_name (for querying metadata), nor does it specify any prerequisites or exclusions. This lack of contextual guidance limits its utility for an AI agent.

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