code_reimbursement

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

No annotations are provided, so the description carries the full burden. It discloses the data source and return types (RVU values, estimated payments), but lacks critical behavioral details such as rate limits, error handling, authentication requirements, or whether the tool performs calculations or fetches pre-computed values. For a tool with no annotation coverage, this is a significant gap.

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, with two efficient sentences that directly state the tool's function and return values. Every sentence adds value without redundancy, making it easy for an agent to parse quickly.

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 moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers purpose and data source but lacks output format details, error conditions, and behavioral context. Without annotations or output schema, the description should do more to compensate, resulting in an adequate but incomplete picture.

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 both parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides (e.g., no examples of code formats beyond schema's 'e.g.', no clarification on auto-detection logic). Baseline 3 is appropriate when the schema does the heavy lifting.

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's purpose with specific verbs ('look up Medicare reimbursement rates') and resources ('medical code'), and distinguishes it from siblings by focusing on reimbursement rates rather than validation, cross-referencing, or other code-related functions. It explicitly mentions what it returns ('RVU values and estimated payment amounts').

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 implies usage for Medicare reimbursement rate lookup, but does not explicitly state when to use this tool versus alternatives like code_lookup or provider_payments. It provides context (CMS PFS conversion factor, 2026 data) but lacks clear exclusions or named alternatives, leaving some ambiguity about tool selection.

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