Score Data

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

Annotations provide little positive behavioral signal since readOnlyHint, idempotentHint, and destructiveHint are all false. The description adds no behavioral detail beyond the core scoring action: it does not clarify whether the operation persists results, executes synchronously, or has side effects. No contradiction exists, but the description does not meaningfully supplement the annotations.

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 wasted words. Every phrase, including 'published' and 'MAS module', carries meaningful selection context, making it an efficiently structured definition.

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?

The input and output schemas are complete, and the description supplies the key published-MAS-module context. However, for a scoring tool with a required step_id and flexible input_data, an agent would benefit from guidance on discovering the correct module step signature and how to obtain module_id in practice.

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 baseline is 3. The description adds only the 'published' qualifier and MAS context, which helps map module_id to a published model or decision, but it does not explain step_id or the structure of input_data beyond what the schema already provides.

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') and a clear resource ('data against a published model or decision (MAS module)'), which conveys the core operation well. It is distinguishable from siblings like run_ml_project or execute_sas_code because it targets published MAS models/decisions, though it does not explicitly name or exclude any sibling alternative.

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 main use case: scoring data against a published model or decision within a MAS module. However, it provides no explicit guidance about when not to use this tool, prerequisites for the published model/decision, or how it compares with related tools such as run_ml_project or get_mas_module_step_signature.

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