list_markets

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the data source (chain trading pools), return fields, and classification methodology. However, it does not mention caching behavior, potential latency, or explicitly state that it is a read-only operation, though these are somewhat implied and partially covered by the schema's refresh parameter.

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 two sentences, front-loaded with the core purpose, and every sentence adds value: source, return fields, and usage priority. No wasted words.

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 low-complexity list tool with 2 well-described parameters and no output schema, the description adequately covers return values and purpose. It could mention result limits or pagination, but given the simple nature and schema coverage, it is sufficiently complete.

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% coverage with both parameters (refresh and includeNonEquity) fully described. The description adds no parameter-specific meaning but also does not need to, as the schema already provides clear semantics. This aligns with the baseline for high schema coverage.

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 what the tool does: lists tokenized stocks on Robinhood Chain, discovered from trading pools. It specifies the returned fields (ticker, contract address, liquidity, and equity classification logic), and positions itself as the entry point for research. This distinguishes it from sibling tools that focus on individual token details.

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 explicitly says 'Call this first to learn what is available to research', providing clear when-to-use guidance. It does not explicitly name alternatives or when not to use, but the 'first' instruction strongly implies a discovery role before using more specific token tools.

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