Multi-pool price sanity gate

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

The description goes well beyond the readOnly/idempotent annotations by disclosing the exact consensus rule (>=2 pools with genuine depth), the fallback behavior (flags single-source or manipulated, lists dissenting pools), and what the tool deliberately does not measure. This gives the agent a realistic model of the tool's behavior and output conditions.

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 tightly structured: a one-line value proposition, a concise behavioral rule, then clear usage guidance and sibling routing. Every sentence earns its place and the most important information 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?

Given the output schema and annotations cover return structure and safety, the description provides everything else needed: purpose, decision rule, failure case, and when-not-to-use guidance. Nothing important is missing for an agent to select and invoke the tool 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?

The description adds no direct meaning about the address or chain parameters; it relies on the schema, where address is described and chain is covered by an enum and default. With 50% schema coverage, this is adequate but not enhanced by the description, so it stays at the baseline.

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 opens with a crisp statement of the tool's sole signal — 'is the quoted price real' — then specifies the mechanism: deriving USD price independently from each deep pool and checking agreement. It clearly differentiates itself from siblings by name and scope, including what it does not measure.

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?

It explicitly states when to use this tool: before quoting, valuing a position, or trusting an oracle reading. It also names the alternatives for adjacent but different concerns, token_depth and honeypot_check, and notes that token_report combines all three. This leaves no ambiguity about tool selection.

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