list_research_atlases

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

No annotations exist, so the description carries the full burden. It discloses ordering (newest first), frequency (one per cycle), content structure (conclusion, changes, evidence), and a setup requirement (ATLAS_API_URL). It doesn't explicitly state read-only nature or rate limits, but for a listing operation this is reasonably transparent.

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?

Two well-structured sentences: first defines the tool's output and ordering, second details item contents and requirement. No filler or repetition.

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?

Despite no output schema, the description explains what each atlas contains and the ordering. Combined with the optional limit parameter in the schema, it fully covers the tool's behavior for an agent to invoke it correctly.

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 only parameter, 'limit', is fully described in the schema with default and range. The description adds no additional parameter semantics, so baseline 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 identifies the resource (research atlases), defines their nature (autonomous analyses of tokenized stocks and RWA ecosystem), and differentiates from sibling market/token tools by focusing on research outputs. The verb is implicit but obvious from the name and context.

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 establishes clear context for when to use it: to retrieve ATLAS agent's published research atlases. It doesn't explicitly name alternatives or exclusions, but the niche is unambiguous given sibling tools are market data, so clear context without exclusions.

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