dex_liquidity

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: it returns specific metrics (e.g., volume_24h_usd) and includes pricing information ('Price: $0.003 USDC per call'), which is useful for cost-aware usage. However, it lacks details on rate limits, error handling, or data freshness, which are important for a financial 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 well-structured and concise, with three distinct sections: purpose statement, usage guidelines, and pricing. Each sentence adds value without redundancy, and information is front-loaded with the core purpose. There's no wasted text, making it highly efficient.

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 tool's complexity (financial data retrieval with 2 parameters), no annotations, and no output schema, the description does a good job of covering key aspects: purpose, usage context, returned metrics, and cost. However, it could be more complete by including details on data sources, update frequency, or error cases, which would help an agent use it more effectively.

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 input schema has 100% description coverage, with clear parameter descriptions (e.g., 'First token symbol'). The description doesn't add any additional semantic details about the parameters beyond what the schema provides, such as format examples or constraints. Since schema coverage is high, the 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's purpose: 'Get liquidity depth and volume for a token pair on DEXs.' It specifies the action ('Get') and resource ('liquidity depth and volume for a token pair on DEXs'), but doesn't explicitly differentiate it from sibling tools like 'token_price' or 'defi_tvl' beyond the DEX focus, which keeps it from a perfect score.

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 includes a 'Use when:' section that provides clear context: 'You need 24h trading volume, market cap, or all-time high for a token pair on decentralized exchanges.' This gives explicit guidance on when to use the tool, but it doesn't mention when not to use it or name specific alternatives among the sibling tools, such as 'token_price' for simpler price data.

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