score_data

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

Annotations are all false, so they do not convey a clear safety or side-effect profile. The description does not disclose whether scoring triggers a remote execution, creates a job, or produces side effects. 'Score data' implies an inference operation, but with readOnlyHint=false the agent cannot confidently assume no state changes.

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, front-loaded sentence with no filler. It states the action, target, and domain efficiently, earning every word.

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 parameter schema is complete and an output schema exists, the tool description is too thin for a compute-oriented operation. It does not mention how to discover required module_id and step_id values via sibling tools like list_mas_modules or get_mas_module_step_signature, nor does it describe execution semantics or potential side effects. The description leaves important workflow context implicit.

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 input schema already documents all three parameters, providing a baseline of 3. The description adds useful semantic framing by specifying that module_id refers to a published model or decision and that input_data is the data being scored, which goes beyond the schema's generic 'MAS module ID' wording.

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 ('score') with a clear resource ('data against a published model or decision (MAS module)'). It distinguishes this tool from siblings like list_mas_modules and get_mas_module_step_signature by stating the actual scoring action.

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 the tool is used when data needs to be scored against a published MAS model or decision, but it does not provide explicit when-to-use/when-not-to-use guidance or reference alternatives. The 'MAS module' qualifier gives some context, but the agent must infer prerequisites like module_id and step_id discovery.

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