crc_lnm_case_data_qc

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

Annotations provide no safety profile (readOnlyHint=false, destructiveHint=false), so the description carries the full burden. It does not disclose whether validation has side effects, what happens on failure, or any specific behavioral traits beyond the generic 'Validate'. This is insufficient for a tool that likely operates on sensitive case data.

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 a single concise sentence with no redundant words. It is front-loaded with the verb 'Validate' and clearly states the three validation dimensions. Every word serves a purpose.

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?

Despite having an output schema, the description omits critical context for a validation tool: it doesn't state the expected inputs beyond the vague 'case', the process, or how results are returned. With 5 required parameters and no schema descriptions, the tool is under-specified for an agent to invoke correctly.

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 0%, and the tool description adds no parameter-level context. It does not explain what 'case_ref', 'input', or other required parameters mean, nor how the 'fallback_policy' and 'ct_source_preference' influence behavior. The description fails to compensate for the absence of schema descriptions.

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 verb ('Validate') and specific scope ('deidentified case integrity, privacy and required modalities'). This distinguishes it from sibling tools like crc_lnm_predict_multimodal and crc_lnm_prepare_ct_features, which focus on prediction and feature preparation rather than data QC.

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 this tool is a preprocessing/validation step before the modeling pipeline, but it does not explicitly state when to use it relative to the sibling tools. No exclusions or alternative recommendations are provided, leaving the usage context to be inferred from the tool name and sibling list.

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