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

No annotations are provided, so the description carries full burden. It describes the output content but does not disclose behavioral traits such as whether the tool is read-only, idempotent, or any side effects. The phrase 'glass-box breakdown' suggests transparency but lacks explicit safety or effect info.

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, well-structured sentence that front-loads the key concept ('Glass-box breakdown') and then lists the included elements. Every word adds value with no redundancy.

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?

Given the tool's complexity (explaining decision logic with sub-signals, weights, etc.) and the absence of an output schema, the description is adequate for high-level understanding but lacks details on the return format or structure. An example or mention of the output shape would improve completeness.

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 coverage is 0%, so the description must compensate. It mentions the parameter 'evaluation_id' in the text but offers no additional details about format, constraints, or examples. While the purpose is clear, the lack of parameter guidance reduces usability.

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 it provides a 'glass-box breakdown' of a prior evaluation, specifying exactly what is included (sub-signal, weight, floor, composite reasoning). This verb-resource combination is specific and distinguishes it from sibling tools like 'alphalabs_evaluate_signal' which focuses on evaluation execution.

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 use after an evaluation by requiring an evaluation_id, but it does not explicitly state when to use this tool versus alternatives like 'alphalabs_calibration_report'. No when-not or alternative tools are mentioned.

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