run_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 adds useful context beyond basic function, such as the timeout behavior (returns queryExecutionId if timeout occurs) and that it returns full results otherwise. However, it lacks details on permissions, rate limits, error handling, or what 'full results' entail, which are important for a mutation-like tool like query execution.

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 sized and front-loaded, consisting of two concise sentences that directly convey the tool's purpose and key behavioral trait (timeout handling). Every sentence earns its place by providing essential information without redundancy or fluff.

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's complexity (executing SQL queries with potential timeouts), lack of annotations, and no output schema, the description is somewhat complete but has gaps. It covers the basic operation and timeout behavior but misses details on output format, error cases, or integration with siblings like get_result, which could aid the agent in proper usage.

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 100%, so the schema already documents all parameters thoroughly. The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't explain query syntax or database naming conventions). Baseline 3 is appropriate as the schema handles the heavy lifting, but the description doesn't compensate with extra insights.

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 specific action ('Execute a SQL query using AWS Athena') and resource (SQL queries), distinguishing it from siblings like get_result (retrieves results), get_status (checks status), list_saved_queries (lists saved queries), and run_saved_query (executes saved queries). It precisely defines what this tool does versus alternatives.

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 clear context for when to use this tool (to execute SQL queries with AWS Athena) and implies when not to use it (e.g., for retrieving results or checking status, which are handled by siblings). However, it does not explicitly name alternatives or state exclusions, such as preferring run_saved_query for saved queries, leaving some guidance implicit.

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