Get Required Baseline Labs

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

Annotations already declare readOnlyHint=true, so the agent knows it's a safe read. The description adds value by describing the output structure (grouped panels with clinical rationale) and noting the PREMIUM tier, which implies access limitations. No contradiction with annotations.

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 three-sentence description is front-loaded with the core function, then usage context, then tier. Every sentence adds value with no fluff, making it highly efficient 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?

For a simple tool with one parameter and read-only annotations, the description covers the key aspects: what it returns (baseline labs grouped with rationale), when to use (pre-treatment workup), and tier. It could be improved by specifying the expected output format more explicitly, but it's largely complete without an output schema.

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 single parameter 'medication' is fully described in the schema (name, id, or alias) with 100% coverage. The description adds no new semantic details about the parameter beyond the schema, so a 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 returns recommended baseline labs/assessments to obtain before prescribing a medication, grouped into panels with clinical rationale. This verb+resource combination is specific and distinguishes it from siblings like get_monitoring_plan (ongoing monitoring) and check_contraindications.

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 to build a pre-treatment workup' and emphasizes 'BEFORE prescribing', providing clear context for when to use. However, it does not explicitly state when not to use it or point to alternatives, though the sibling list and phrasing imply differentiation from post-prescription tools.

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