Compute AI Trust Score

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety and determinism profile is covered. The description adds useful context by disclosing the output shape (0-100 score, A-F grade, LOW-to-CRITICAL risk tier), but says nothing about weighting, determinism of the composite, or how missing dimensions are treated.

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?

Two tightly written sentences: the first states the computation and its dimensional scope, the second the return values. No filler and the core purpose is front-loaded.

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?

For a no-output-schema tool the description does cover the return contract, and annotations cover safety. What is missing is the input scale/default behavior for six undocumented parameters and any differentiation from the sibling rai_check_trust, which is the main thing an agent needs to choose 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%, so the description carries the burden, and it partially does by naming the same six dimensions as the parameters. However, it never explains that inputs are 0-1 normalized (while the output is 0-100), that all six default to 0.5, or how the dimensions are weighted, so the semantics of the actual inputs remain under-specified.

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 names a specific verb and resource ('Compute a composite AI Trust Score') and enumerates the six governance dimensions and the output artifacts (score, letter grade, risk tier). It is clear what the tool does, but it never distinguishes itself from the close sibling rai_check_trust, leaving the agent to guess which trust-scoring tool to pick.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives. With a near-identical sibling (rai_check_trust) in the toolset, the absence of routing criteria is a real gap rather than a minor omission.

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