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

With no annotations provided, the description carries the full burden. It discloses the data source, the chains covered, the time window, the outcome categories, and the cost ($0.01 USDC). It does not disclose rate limits, whether the payment is required or optional, or what happens if the address has no history. The payment mention is useful but incomplete because the schema has a nullable payment parameter with default null.

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 a single dense paragraph that front-loads the core purpose and includes the key facts (chains, date, outcome types, cost). It is slightly long but every clause adds information. The structure could be improved by separating the cost and data-source note, but it is not bloated.

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?

The tool has an output schema, so return values are covered elsewhere. The description covers the main query intent, data source, and cost. However, it lacks guidance on the payment parameter (required vs optional, how it is used), and it does not mention edge cases like unknown addresses or unsupported chains. For a paid data-lookup tool with no annotations, this is a moderate gap.

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?

Schema description coverage is 0%, so the description must compensate. It explains the meaning of 'address' (the deployer) and 'chain' implicitly by naming the supported chains, but it does not explain the 'payment' parameter at all, nor does it specify expected formats (e.g., checksummed address, chain name vs chain ID). The description adds context about the data but leaves parameter-level semantics largely to inference.

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 ('Answers has this deployer rugged before?') and a specific resource (deployer launch history from CurveCall's hourly launch-outcome index). It clearly distinguishes itself from siblings like token_risk or wallet_snapshot by focusing on deployer-level history and outcome flags. The scope (chains, since date, outcome categories) is explicit.

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 implies when to use it: when you need to know a deployer's past launch outcomes and rug rate. It names the data source and the question it answers, which gives clear context. However, it does not explicitly state when NOT to use it or name alternative tools for related queries (e.g., token_risk for a specific token's risk), so it falls just short of a 5.

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