get_token_prices

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

With no annotations provided, the description carries full behavioral disclosure burden. It reveals that current prices use Aftermath with Pyth as fallback, and historical prices rely on the Pyth oracle at the given time, which provides meaningful insight into data source reliability. However, it does not mention failure modes (e.g., what happens if a price is unavailable) or rate limits.

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 extremely concise, using three short sentences to convey the primary purpose, data source behavior, and input format. Every sentence adds value with no fluff, and the most important information (what it does) 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 read-only price query tool with no output schema, the description covers the core functionality, historical vs. current behavior, data sources, and required input format. It lacks explicit return structure (e.g., mapping from coin type to price) but the simplicity of the tool makes this acceptable. The network parameter is not mentioned in the description, though it is thoroughly documented in the schema.

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?

All parameters are fully described in the schema (100% coverage), so the description adds only redundant reinforcement (e.g., 'Accepts full coin type strings'). It does not provide new semantic meaning beyond the schema, such as return format or unit details, so a baseline score 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 clearly states the tool gets USD prices for Sui tokens, with a specific distinction between current and historical prices via the `at` parameter. It also specifies the data sources (Aftermath, Pyth) and input format, making it distinct from sibling tools like get_balance or analyze_token.

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 explains when to use current vs. historical modes (when `at` is set) but does not explicitly compare against alternative sibling tools like analyze_token. It provides context on data source fallback but lacks explicit 'use this when' or 'instead of' guidance.

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