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

Annotations already declare readOnlyHint=true, and the description adds behavioral context by revealing that data is pre-warmed and guaranteed, which implies a fast, reliable read. It does not go into authorization or pagination, but with annotations covering the safety profile, this is acceptable.

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, with the core definition front-loaded. Every word adds value, and it avoids restating the title or schema. This is efficient and well-structured.

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 listing tool with no output schema, the description provides enough context: what the tool returns (a directory of symbols) and why one would use it. It does not specify the response structure, but given the simple nature and strong annotations, this is sufficient.

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 100%, so all three parameters (sort, limit, apiKey) are already well-documented in the input schema. The description adds no additional parameter-level meaning, aligning with the baseline score of 3.

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 provides a curated tier-1/tier-2 symbol directory, with specific detail about pre-warmed data. This distinguishes it from sibling tools like get_symbols or get_tickers by emphasizing the curated and guaranteed-warm nature, making the purpose and differentiation clear.

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 lists three use cases: discovering symbols with warm data, checking coverage before subscribing, and enumerating the universe for cross-sectional scans. While it does not name alternatives or explicitly state when not to use, the use-case guidance is concrete and helpful.

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