lerg_complex_query

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description does not need to cover safety. It lists supported filter operators and shows a join example, but does not disclose additional behavioral traits like performance or caching. This is adequate but minimal extra context.

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 three sentences with no wasted words: first sentence states purpose, second lists operators, third gives usage guidance. It is front-loaded and efficient.

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 (6 parameters, nested objects, no output schema), the description covers the core use case and operators. However, it does not mention behavior for pagination (limit/offset) or return format. Annotations fill some gaps, making it reasonably 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?

Schema description coverage is 100%, so baseline is 3. The description adds value by providing concrete examples of filter syntax (e.g., [{field:'npa', operator:'eq', value:720}]) and a join example (lerg_6 with lerg_1 via OCN). This helps agents understand parameter usage beyond the schema.

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 'Execute a complex LERG query with JOINs across multiple tables', providing a specific verb and resource, and distinguishes from siblings like lerg_query by emphasizing complexity and joins. An example (joining lerg_6 with lerg_1 via OCN) further clarifies the tool's purpose.

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 explicitly says 'Use this when you need to combine data from different LERG tables', which gives clear context for when to use it. While it does not list when not to use it or explicit alternatives, the contrast with simpler siblings is implied.

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