crc_lnm_prepare_pathology_features

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

With no annotations indicating safety hints, the description carries the full burden of behavioral disclosure. It says 'validate and retain,' implying a side effect, but does not disclose prerequisites (beyond 'approved'), failure modes, or what 'retain' means operationally. No detail is given about the validation criteria or what happens to rejected features.

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, tightly-written sentence that is front-loaded with the action. Every word contributes to the meaning, and there is no fluff. However, the brevity sacrifices essential detail, so it is not a 5.

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?

Although the tool has an output schema and sibling tools suggest a multi-step pipeline (QC → prepare → predict → report), the description provides no context on where this tool fits. It does not mention that it is a prerequisite for prediction or that it consumes QC'd artifacts. A minimal complete description should place it in the workflow.

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 description adds no parameter-specific meaning. The input schema has five parameters (e.g., qc_artifact_id with a pattern but no description), and the tool description does not explain the role of qc_artifact_id or the contract fields. With 0% schema description coverage, the description should compensate but does not.

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 uses a specific verb ('Validate and retain') and resource ('pathology features') with a precise dimension (768-dimensional), clearly distinguishing it from the sibling tool crc_lnm_prepare_ct_features. However, it does not explicitly contrast with other tools or mention the pipeline context, so it stops short of a 5.

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 no guidance on when to use this tool vs alternatives. It does not mention that this is for pathology (vs CT), nor that it should be run after QC. The schema contains a Chinese note about only accepting QC'd artifacts, but the description itself offers no usage direction.

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