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

With no annotations, the description carries the full burden. It discloses what the tool does in detail: returns every token with that symbol, liquidity-ranked, flags the dominant/likely-real one, and for addresses tells rank. It clearly implies a read-only lookup with no side effects. It doesn't cover rate limits or error conditions, but for a simple lookup this is sufficient.

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 three sentences and front-loaded with the core purpose. It includes a concrete example ('19 tokens named GP') and explains the problem, which is useful context. Slightly verbose with the 'runner problem' explanation, but every part contributes to understanding.

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 a simple 1-parameter tool with no output schema, the description covers input, output behavior, and use case well. It doesn't specify the exact return format (e.g., JSON structure or field names), but it does explain key output features like liquidity ranking and flagging, which is adequate for an agent to invoke and interpret results.

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 schema describes the single parameter ('query') as a token symbol or address, providing 100% coverage. The description adds valuable context on how the parameter is used and what behavior changes when an address is passed versus a symbol, enhancing the schema's meaning.

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 uses a specific verb ('Find') with a clear resource ('COPYCAT tokens on Robinhood Chain') and explains the underlying problem. It clearly differentiates from sibling tools like robinhood_authenticity or token_security by focusing on clones/imposters sharing a name/symbol.

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 gives an explicit use case: 'Use for is this the real X on Robinhood / are there fakes'. It also states inputs ('Give a symbol or a 0x address'). It doesn't explicitly mention when not to use it or name alternatives, which keeps it from a 5.

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