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

With no annotations, the description carries the full behavioral burden and does so well: it names the independent sources, explains the median/deviation/severity logic, discloses source-disagreement and error handling, and states the failure and billing behavior. This is unusually transparent for a read-only data tool.

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 dense but front-loaded: it begins with the tool's identity, then compresses sources, outputs, severity thresholds, errors, and cost into a single purposeful paragraph. Every clause adds useful information and there is no filler.

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 no output schema and no annotations, the description supplies the output fields, severity taxonomy, error behavior, and pricing model needed to invoke and interpret the tool. Nothing essential for a one-optional-parameter peg monitor is missing.

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 sole parameter is fully documented in the schema, and the description repeats the supported coin list rather than adding new semantics such as normalization rules or invalid-input behavior. With 100% schema coverage, the baseline of 3 is appropriate.

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 states a specific verb and resource: checking USD stablecoin pegs against $1 across named sources. It also names the exact coins and the peg-specific outputs, which clearly distinguishes it from generic price or pair-data siblings.

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 context strongly implies that this tool is for stablecoin depeg monitoring, but the description never explicitly says when to use it instead of siblings like crypto_price, token_price, or pair_data. Usage is inferable rather than stated.

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