enabiz_list_lab_tests

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

Beyond readOnlyHint and openWorldHint annotations, description discloses hazards (large response without query), auth requirement, error format, and grouping behavior. No contradictions.

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?

Well-structured bullet points, each sentence adds value. No redundancy. Front-loaded with main purpose then parameter details.

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 (listing, filtering, truncation, auth) and presence of output schema, description covers return grouping, truncated flag, and error handling. Complete for effective use.

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?

All 4 parameters are fully explained with default behaviors and usage tips (e.g., limit default 50, test_query for filtering). Schema has 0% description coverage, so description adds all necessary meaning.

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?

Description clearly states 'list lab test results by year range'. The tool name and description specify lab tests, distinguishing it from siblings like enabiz_list_medications or enabiz_list_vaccinations.

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?

Provides clear usage context: default year range, recommendation to use test_query for specific tests to avoid large responses, and explains what to do if truncated. Lacks explicit when-not-to-use but is sufficient.

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