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

With no annotations, the description carries the full burden. It discloses that the tool is FREE, lists the three categories of returned data, and explains the merkle-commit anti-curation property. It does not describe exact response formatting or limitations, but for a zero-parameter public scorecard it provides solid behavioral context.

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 well-organized, with the core purpose front-loaded and a clear 'Use this when' section. The parenthetical example and merkle-commit explanation add trust-relevant detail, though the description is slightly more verbose than strictly necessary.

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 simple zero-parameter tool with no output schema, the description explains what will be returned and why it can be trusted. It lacks an exact response structure, but an agent can confidently invoke the tool and understand the high-level result contents.

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 tool has zero parameters and an empty input schema, so parameter semantics are not applicable. Per the baseline for 0-parameter tools, a score of 4 is appropriate; the description does not need to compensate for parameter documentation gaps.

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 clear verb 'Returns' and identifies a specific resource: the oracle's public accuracy scorecard. It lists concrete contents (conformal coverage, on-chain track record, blind study), making the tool's purpose clear. It does not explicitly distinguish itself from sibling tool check_accuracy, but the scorecard framing is distinct enough.

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 explicitly states when to use it: when an agent wants evidence that calibration claims are real, or for a trust-but-verify check before paying for forecasts or loan terms. This is strong contextual guidance, but it does not mention when not to use it or name alternative siblings.

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