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

Annotations already cover safety (readOnlyHint, openWorldHint), so the description focuses on added value: the exact return fields and a realistic example response. It also notes the per-call price. It doesn't discuss rate limits or caching, but for a simple read-only public price query the disclosure is solid.

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?

Front-loaded purpose followed by tightly labeled sections (Use when, Not for, Returns, Example). Every sentence earns its place; 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?

No output schema exists, and the description compensates by listing return fields and a concrete example. Usage routing, return shape, and pricing are all present, making it complete for this tool.

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?

With 100% schema description coverage and a single documented parameter, the schema carries the semantics. The description adds no syntax or formatting guidance beyond the schema's example (BTC, ETH, SOL). Baseline 3 is correct.

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?

States a specific verb and resource ('Get the current USD price of any cryptocurrency token') and explicitly distinguishes itself from three named siblings via the 'Not for' section. An agent can select it unambiguously.

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?

Provides explicit 'Use when' criteria (price, 24h change, market cap) and 'Not for' exclusions routing to token_market_data, market_snapshot, and orderbook_depth. No inference required.

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