query_raw_logs

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 clearly states the tool is 'read-only' and specifies 'Only read operations are allowed,' which covers safety and permissions. It also lists available tables, providing context about what data can be accessed. However, it lacks details on rate limits, error handling, or response format, preventing a perfect score.

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, starting with the core purpose, followed by available tables and parameter details. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 (SQL querying with multiple tables), no annotations, and an output schema present (which handles return values), the description is largely complete. It covers purpose, usage, behavioral constraints, and parameter semantics. However, it could benefit from mentioning query limitations (e.g., timeouts, result size) or authentication needs, slightly reducing completeness.

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 0%, so the description must fully compensate. It explicitly defines the single parameter 'query' as 'A SELECT SQL query' and adds critical constraints ('Only read operations are allowed'), providing essential semantic meaning beyond the bare schema. This fully addresses the parameter's purpose and 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 the specific action ('Run a read-only SQL query') and target resource ('against the health database'), distinguishing it from sibling tools that perform calculations, summaries, task management, or scheduling. It precisely defines the tool's function without being vague or tautological.

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 (for SQL queries on health data) and implicitly suggests alternatives by listing available tables, but it does not explicitly state when not to use it or name specific sibling tools as alternatives. This gives good guidance but falls short of the highest score.

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