lookup_dicom_tag

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 effectively compensates for the missing output schema by explicitly listing all returned fields (tag number, name, VR, VM, description, common values, usage notes), giving the agent clear expectations about the tool's output structure.

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 tightly structured with three distinct information units: purpose (sentence 1), return values (sentence 2), and input formats (sentence 3). Every clause earns its place with zero redundancy or filler text, presenting information in order of operational importance.

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 single-parameter lookup tool with no annotations, the description is complete. It covers the tool's function, input flexibility, and return structure comprehensively. The absence of an output schema is adequately mitigated by the detailed return value description, making this sufficient for correct agent invocation.

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?

While the schema has 100% coverage and documents the basic parameter, the description adds valuable semantic context by specifying additional valid input formats, particularly the parenthetical syntax '(0010,0010)' which supplements the schema's examples. This helps the agent understand the flexible parsing capabilities.

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 (Look up), target resource (DICOM tag), and input methods (group/element number or keyword). It effectively distinguishes from siblings like pacs_query (which retrieves studies) and decode_private_tags (specific to private tags) by focusing on standard tag dictionary lookup.

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 implied usage guidance through detailed input format examples ('0010,0010', '(0010,0010)', 'PatientName'), helping the agent construct valid inputs. However, it lacks explicit differentiation from the sibling explain_dicom_tag tool or clear when-to-use/when-not-to-use guidance.

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